ABSTRACT BOYD, SHELBY KATHERINE. Interlayer Chemistry

ABSTRACT

BOYD, SHELBY KATHERINE. Interlayer Chemistry and Energy Storage Mechanisms of Manganese-Rich Oxides in Aqueous Electrolytes. (Under the direction of Dr. Veronica Augustyn).

Electrochemical alkali metal cation insertion from aqueous electrolytes into transition metal (TM) oxides is appealing for low-cost and safe electrochemical energy storage (EES), desalination, and element recovery. The strong interactions between water, electrolyte salts, and

TM oxide surfaces dictate the material stability and EES mechanisms. However, these are not yet understood well enough to enable large scale long-life neutral-pH aqueous EES. To advance this understanding I synthesized micron-sized and nanostructured layered manganese-rich oxides and determined how their interlayer environment effects their structural and electrochemical behavior in aqueous electrolytes. First, by tuning the TM content. Second, by tuning the amount of interlayer water. And third, by determining the mechanisms of pseudocapacitive behavior in nanostructured birnessite MnO2.

The effect of TM composition on P2 layered Na+ manganese-rich oxides has been extensively investigated for non-aqueous electrolytes, but not aqueous electrolytes. In Chapter 2,

I synthesize the following series of P2 oxides and characterize their structural stability upon aqueous electrochemistry: Na0.62Ni0.22Mn0.66Fe0.10O2, Na0.61Ni0.22Mn0.66Co0.10O2,

Na0.64Ni0.22Mn0.66Cu0.11O2, and Na0.64Mn0.62Cu0.31O2. Electrochemistry and ex situ X-ray diffraction (XRD) show that water intercalation upon interlayer Na+ removal causes an irreversible phase transformation in all compositions, although transformation extent depends on TM composition and the maximum anodic potential. The 25% c-axis expansion causes eventual electrode failure due to loss of electronic connectivity and particle delamination. These first studies on the structural effects of aqueous electrochemistry in P2 oxides show the significance of TM composition on interlayer water affinity.

The capacitive electrochemical behavior of hydrated P2 oxides suggested that these particles have potential for high power EES. Chapter 3 describes my in situ synchrotron XRD investigation of the water insertion mechanism, and the scalable “top-down” strategy I subsequently developed to electrochemically expand micron-scale P2 oxides. I hypothesize that the electrochemical expansion produces a promising electrochemical capacitor material by two changes: (1) interlayer hydration, which improves interlayer diffusion kinetics and buffers intercalation-induced structural changes, and (2) particle expansion, which significantly improves electrode integrity and volumetric capacitance. Compared with commercially available activated carbon, the expanded materials have higher volumetric capacitance at charge/discharge timescales

≥40 seconds. Therefore hydrating the interlayer of large manganese-rich oxide particles makes them viable for high power electrodes.

To conclude my study of the effect of interlayer environment on the electrochemical and structural behavior of layered manganese-rich oxides, I investigated the nature of capacitive charge storage in nanostructured birnessite δ-MnO2. Whether capacitance in birnessite is due to non- faradaic (double layer) or faradaic (pseudocapacitive) behavior is a topic of debate. In Chapter 4,

I used ex situ XRD, electrochemical quartz crystal microbalance (EQCM), in situ Raman spectroscopy, and operando atomic force microscope (AFM) dilatometry to observe the electronic, vibrational, structural, gravimetric, and mechanical response of birnessite during electrochemical cycling in an aqueous electrolyte. XRD and Raman spectroscopy showed significant interlayer contributions likely due to faradaic processes. EQCM showed that a combination of ions and water molecules were involved in the complex energy storage mechanism. AFM showed that while the interlayer expands upon ion removal, the electrode as a whole contracts. In addition, this was the first electrochemical AFM dilatometry study on a material undergoing interlayer ion insertion.

Overall, this study showed that capacitive energy storage in birnessite MnO2 involves ion intercalation into the interlayer in a capacitive charge storage process. Based on experimental and simulation results, we hypothesize that nanoconfinement within the hydrated interlayer blurs the distinction between pseudocapacitive and electrical double layer processes.

Overall, my dissertation showed how to tune the electrochemical response and interlayer chemistry of manganese-rich oxides and their mechanism of charge storage in aqueous electrolytes. These results are promising for obtaining high power EES with low cost, sustainable metal oxides as well as fundamental understanding of electrochemical behavior under confinement. I discovered the role of transition metal composition on the stability of sodium manganese-rich oxides in aqueous electrolytes. I developed a scalable synthesis to electrochemically expand and hydrate large transition metal oxide particles for high volumetric capacity electrodes. Finally, I conducted a multi-modal study to address a major fundamental question of aqueous EES, determining that capacitive charge storage in birnessite originates from a complex mechanism involving (de)insertion of both ions and water molecules in the interlayer, where nanoconfinement blurs the distinction between pseudocapacitive and double layer capacitive mechanisms.

by Shelby Katherine Boyd

A dissertation submitted to the Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy

Materials Science and Engineering

Raleigh, North Carolina 2020

APPROVED BY:

______Veronica Augustyn James Martin Committee Chair

______Joseph Tracy Albena Ivanisevic

BIOGRAPHY

I grew up on the ocean side of the San Francisco Bay Peninsula, where it was foggy and chilly most of the time—not your typical image of California. In 2011 I moved to San Luis Obispo,

CA, and began my B.S. in Materials Engineering at California Polytechnic State University San

Luis Obispo. While living in SLO, I was fortunate to find a good community of friends both at my church and on campus, and heavily benefitted from the abundance of student-run clubs. My first year I joined the amateur high-powered rocketry club, where I made and successfully launched my own rocket. My junior year I joined the Underwater Remotely Operated Vehicle (UROV) robotics club project as an excuse to learn more machine shop skills.

I had several summer internships while a student in the industry-focused Materials

Engineering program. One memorable moment from my first internship in 2012 is the day my boss told me to polish the edges of laser-cut plastic to a shine. Little did I know that those couple of days at a buffing wheel were preparing me for every job since then: tasked with using an unfamiliar process with indeterminate variables, I had to just keep trying until I was successful.

This story (and the machine shop class I took) helped me get an internship with Apple. I spent the summer of 2013 machining and polishing aluminum plaques for surface texture development, which really was more fun than it sounds. Curious about how the aluminum stock was made, my next internship (the one that cemented my plan to go to grad school) was with Sapa Extrusions in

Phoenix, AZ in 2014. This was my first experience living outside of CA and dealing with extreme weather. During my last year at Cal Poly, my role in the robotics club was by far the highlight. As part of UROV team, I helped take our robot Santiago from the very first design all the way to competing internationally in Canada. We came in second-to-last, and after all the struggles to get there, I could not have been happier.

After graduating in 2015, I received my first formal introduction to electrochemistry in the form of nickel electroplating during a co-op with Apple’s power adapter manufacturing team. I then began my Ph.D. work with Veronica Augustyn in January 2016. Starting scientific research was not an easy shift in mindset from my previous manufacturing experience. While the various colors of transition metal oxides in solution provided some amount of joy, I also prioritized running, reading books for fun, and attending and serving in my church throughout my graduate studies. Together, these provided valuable grounding, relationships, and personal growth.

My first research project is described in Chapter 2. This work holds a special place in my heart. The nine months I spent learning to prevent my electrochemical cells from rusting overnight are a bit unforgettable, as was finding out 1.5 years into the project that my starting assumption was completely wrong (the materials were not stable in air or water).

In 2018, I was roommates with Natalie Geise at the Gordon Research Conference on

Batteries, which led into the collaboration in Chapter 3. Her advisor, Mike Toney, ran a group doing electrochemistry at the Stanford Synchrotron Radiation Lightsource. They had the ability to do aqueous electrochemistry and in situ synchrotron XRD, which allowed us to observe the mechanism of particle expansion upon electrochemistry (see Chapter 3). One of the more encouraging moments of my Ph.D. was Mike’s enthusiastic “we can do that!” when we first discussed the project over breakfast. The Gordon Conference and the Next Generation

Electrochemistry (NGenE) workshop in June 2018 were my favorite events I attended as a graduate student. In both situations, the small group of people and concentrated time together really facilitated building collaborations. After NGenE, I collaborated with Gene Nolis at the University of Illinois at Chicago on using P2 oxides as Mg2+ cathodes until he graduated. While our work did not result in a publication, it was a great collaborative experience.

iii

Chapter 4 represents the culmination of my time in graduate school—I applied all my existing knowledge, learned new experimental and analysis techniques, and developed the biggest collaboration I had yet to be a part of. Over four trips out to Oak Ridge National Lab, I became surprisingly fond of that 6+ hour trip—having good collaborators there definitely helped. In addition, I finally started to get comfortable with Matlab because the atomic force microscopy

(AFM) data needed to be worked up via script, and I had to re-write a script initially written by my colleague Dr. Ruocun (John) Wang. Working through this then gave me the confidence to adapt it for handling the electrochemical quartz crystal microbalance (EQCM) data.

Each year had a few defining moments outside of research. During my first year I helped establish SciBridge as a student organization at NC State. The second year was a whirlwind of taking the qualifier exam, being awarded the NSF GRFP, and a research exchange where I spent six weeks in Wollongong, Australia. Not much research got done due to the short time I was there, but my ocean-loving heart was happy living right next to the beach. During my third year I slowly began to love North Carolina, and my career goals switched from industrial R&D to teaching. This was bolstered by professional development programs in the Graduate School’s Teaching and

Communication Certificate, which provided an avenue to develop valuable non-scientific skills and interact with students from a variety of disciplines. My fourth year saw more trips to Oak

Ridge, as well as wedding planning. After wrapping up my Ph.D. in Materials Science, I plan to take a postdoctoral research position in the Chemistry Department at NC State.

ACKNOWLEDGMENTS

“If you want to go fast, go alone. If you want to go far, go together.” (unknown)

The Ph.D. journey is not an easy one, and I could not have done mine without the support of many people from across the world. I am extremely thankful for all the people God has put in my life throughout the last several years. Especially my husband Naveen, who teaches me grace, convinced me of the importance of sleep, and helps me see the bigger picture in life.

To my advisor Veronica Augustyn, thank you for all of your support and using your skills as an excellent scientist to train me how to be a scientist myself, as well as for letting me help teach

MSE 791. To each of my committee members: Joe Tracy, Jim Martin, Albena Ivanisevic, thank you for your time, advice, and insight into my research. To my research group colleagues, John,

James, Mike, Simon, Ishita, Saeed, and Matthew: each of you are excellent scientists and fantastic people. I am so thankful for the chance to work together and all the input you gave about my research. I’ll miss you all. To Kevin, who helped me with the birnessite project and really did

“save the world” (got the project off its feet), thank you. To Dr. Vanessa Doriott Anderson, and her colleagues at The Graduate School, thank you for providing fantastic professional development resources, and your support along the way. To the custodial, department, facilities, and AIF staff, unending thanks for all you do to keep things running in the department.

To all the superb scientists I had the opportunity to collaborate with, thank you. Dr. Nina

Balke and Dr. Wan-Yu Tsai at Oak Ridge National Lab, for being truly amazing scientists and making the long days in the AFM lab enjoyable. Dr. Mike Toney and Natalie Geise at Stanford and the SLAC National Lab. Mike for supporting our idea, and Natalie for wholeheartedly supporting my project during our beam time and while analyzing data. Dr. Jordi Cabana and Dr.

Gene Nolis at University of Illinois Chicago, for exploring the possibility of P2 oxides as a Mg2+

cathode and going down the rabbit holes trying to understand our data. Dr. Adri van Duin and

Karthik Ganeshan at Pennsylvania State University, for suffering through modeling manganese for the birnessite project, and coming up with cool results. Dr. Jon-Paul Maria, now at Penn State, who let me do endless XRD for the P2 project. Dr. Shulei Chou and Dr. Yunxiao Wang, who hosted me at the Institute for Semiconducting and Electronic Materials at the University of

Wollongong. Dr. James LeBeau and Dr. Rohan Dhall, who collaborated with us on the STEM in

Chapter 2.

I would like to thank those who financially supported my research as well. The National

Science Foundation Graduate Research Fellowship Program Grant No. 571800 supported me for most of my Ph.D. The Fluid Interface Reactions, Structures and Transport (FIRST) Center, an

Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science,

Office of Basic Energy Sciences, for supporting materials and characterization after the project in

Chapter 2. The University Global Partnership Network for supporting the research exchange with

University of Wollongong. The College of Engineering and the Graduate School for travel awards, and the College of Engineering for the McNeill Fellowship and the Mentored Teaching

Fellowship.

I would also like to thank my family for supporting me when I moved across the country for graduate school, and their love and support since. Thank you to my Raleigh family at Vintage

Church, especially Mark Woodwell, Josh and Savannah Carroll, Denise Welling, Melissa Almond, and Tyler Jones for their consistent kindness, grace, and mentorship, and my community group for bearing with me through all the ups and downs. Thank you to Dr. Helen Holmlund for being a fantastic friend and long-distance grad school support buddy. Thank you to Aubrey Penn, Hannah

Dedmon, and Madaline Logan for your friendship and community. Thank you to Cynthia Koehler

for being both a friend and enabler of crazy lab ideas. Thank you to all my college friends who are up for talking after months of silence. To everyone who encouraged me to apply to graduate school and just go for the Ph.D., thank you for believing in me. Most of all, thank you to God for designing such a crazy beautiful world, and giving us the tools to investigate it. The stones really do cry out in praise. Finally, I would like to thank the three pairs of running shoes I’ve gone through in the last 4.5 years (the number of pairs should probably be higher), the bottles of bug spray, and everyone who maintains Raleigh’s sidewalks and greenways and lets me keep running.

vii

TABLE OF CONTENTS

LIST OF TABLES ...... x LIST OF FIGURES ...... xi Chapter 1: Motivation and Background...... 1 1.0 Introduction ...... 1 1.1 Energy Storage Mechanisms...... 3 1.2 Aqueous Electrolytes ...... 8 1.3 Manganese Oxides ...... 14 1.3.1 Manganese Dioxide ...... 14 1.3.1.1 Amorphous MnO2 ...... 16 1.3.1.2 Hollandite (2x2) Tunneled α-MnO2 ...... 16 1.3.1.3 Spinel λ-MnO2 ...... 17 1.3.1.4 Birnessite δ-MnO2...... 18 1.3.1.5 Intergrowth γ-MnO2 ...... 20 1.3.2 Manganese-Based Oxides ...... 21 1.3.2.1 Tunnel-Structured NaxMO2 ...... 23 1.3.2.2 Layered P2 NaxMO2 ...... 25 1.4 Tuning Material Behavior Post-Synthesis ...... 27 1.5 Summary ...... 28

Chapter 2: Charge Storage Mechanism and Degradation of P2-Type Sodium Transition Metal Oxides in Aqueous Electrolytes ...... 30 2.1 Abstract ...... 31 2.2 Introduction ...... 32 2.3 Methods...... 34 2.3.1 Material Synthesis ...... 34 2.3.2 Physical Characterization ...... 35 2.3.3 Electrochemical Characterization ...... 36 2.4 Results and Discussion ...... 38 2.4.1 General Results ...... 38 2.4.2 Role of Transition Metal Composition on the Interlayer Affinity for Water ...... 42 2.4.3 High pH Electrochemistry ...... 53 2.4.4 Effect of Potential Window on the Interlayer Affinity for Water of P2 Oxides in Aqueous Electrolytes ...... 56 2.4.5 Electrochemical Impedance Spectroscopy ...... 61 2.5 Conclusions ...... 64 2.6 Conflict of Interest ...... 65 2.7 Acknowledgements ...... 65

Chapter 3: High Power Energy Storage via Electrochemically Expanded and Hydrated Manganese Oxides ...... 66 3.1 Abstract ...... 67 3.2 Introduction ...... 67 3.3 Materials and Methods ...... 70

viii

3.3.1 Material Synthesis: Bulk Powders ...... 70 3.3.2 Material Synthesis: Electrochemical Expansion ...... 71 3.3.3 Methods: Synchrotron X-ray Diffraction...... 72 3.3.4 Methods: Physical Characterization ...... 73 3.3.5 Methods: Electrochemical Characterization ...... 73 3.4 Results and Discussion ...... 75 3.4.1 Mechanism of Electrochemical Expansion ...... 75 3.4.2 Batch Expansion Process ...... 80 3.4.3 Structural Characterization of Expanded Materials ...... 82 3.4.4 Electrochemical Behavior of Expanded Materials ...... 84 3.4.5 Comparison of Expanded NaMCu to Commercial Activated Carbon ...... 92 3.5 Conclusions ...... 94 3.6 Acknowledgements ...... 95 3.7 Author Contributions Statement ...... 95 3.8 Conflict of Interest Statement ...... 96

Chapter 4: Redox or Double Layer? Interlayer Confinement Blurs the Horizon Between Faradaic and Non-Faradaic Charge Storage in Birnessite ...... 97 4.1 Abstract ...... 98 4.2 Introduction ...... 98 4.3 Methods...... 103 4.3.1 Electrodeposition of Birnessite ...... 103 4.3.2 Physical Characterization ...... 104 4.3.3 Electrochemistry ...... 104 4.3.4 In situ Raman Spectroscopy ...... 105 4.3.5 Operando Atomic Force Microscopy (AFM) Dilatometry ...... 105 4.3.6 Electrochemical Quartz Crystal Microbalance (EQCM) Measurements .. 107 4.3.7 EQCM Calibration ...... 107 4.3.8 Applicability of EQCM to Thin Films ...... 109 4.4 Results and Discussion ...... 109 4.4.1 Global Techniques: Electrochemistry, Ex situ XRD, and EQCM ...... 112 4.4.2 Local Techniques: In Situ Raman Spectroscopy and Operando AFM ..... 119 4.3.3 Rate-Dependence of AFM and EQCM Data ...... 127 4.5 Conclusions ...... 132 4.6 Acknowledgements ...... 132

Chapter 5: Summary and Outlook ...... 134

References ...... 139

Appendices ...... 168 Appendix A: Synthesis of Large Crystalline Birnessite Flakes ...... 169 Appendix B: Matlab Codes ...... 176 Appendix C: Peak Fitting Instructions for Birnessite Data ...... 211 Appendix D: Effect of Film Thickness on the Behavior of Birnessite ...... 222

LIST OF TABLES

Chapter 1 Table I Radii of Alkali Cations in Aqueous Electrolytes ...... 13

Chapter 2 Table I Composition (from ICP-OES) and lattice parameters (from Rietveld refinement) of the P2-type Na0.6Mn0.66M0.34O2 ...... 39

Table II Interlayer spacing of the four compositions of P2 oxides measured with XRD and STEM for pristine, water-exposed, and electrochemically cycled samples ...... 44

Table III Raw data for the interlayer spacing calculations from STEM images ...... 45

Table IV Anodic capacities and Coulombic efficiencies of the four compositions -1 of P2 oxides in 1 M aqueous Na2SO4 electrolyte cycled at 0.1 mV s ...... 51

Table V Calculated redox peak shifts (from E°) for Na+ or H+ intercalation as a function of increasing electrolyte pH ...... 54

Table VI Calculated values for Rs, Rct, and D for NaNMCo and NaMCu before and after cycling to 0.8 V vs. Ag/AgCl ...... 62

Chapter 4 Table I Mass-charge ratios of birnessite in K2SO4 and Li2SO4 at 10 mV/s ...... 117

Appendix B Table I Inputs for QCM Solver ...... 205

Appendix D Table I Summary of Birnessite EQCM Results from Literature ...... 223

LIST OF FIGURES

Chapter 1 Figure 1 Characteristic electrochemical shapes of an A) Nernstian faradaic redox couple showing reversible peaks and low background current in regions away from the redox peak. B) A non-faradaic EDL capacitance response showing a constant current across the potential window...... 6

Figure 2 A) Gouy-Chapman-Stern model of the electric double layer at a transition metal oxide/aqueous electrolyte interface. The electrochemical potential at the electrode-electrolyte interface decreases linearly across the Stern layer thickness (dStern), where the coordinated waters of the Inner Helmholtz Plane (IHP) and hydrated cations of the Outer Helmholtz Plane (OHP) form a structured layer of water at the interface. B) Reactivity of water demonstrated by a Pourbaix (potential vs. pH) diagram of water showing the thermodynamically stable region. The upper (red) dashed line represents the OER, and the lower (blue) dashed line shows the HER. Reproduced from Ref. 1 by permission of The Royal Society of Chemistry...... 10

Figure 3 Strong interactions of aqueous electrolytes with a hydrated layered transition metal oxide, including surface coordination and hydration by free waters...... 11

Figure 4 The challenges and prospects of aqueous electrolytes for EES devices. If the hurdles of gas evolution, low voltage, and material dissolution can be overcome, low cost, high power, and sustainable EES awaits. Reproduced from Ref. 1 by permission of The Royal Society of Chemistry...... 13

Figure 5 Common polymorphs of MnO2, where MnO6 octahedra are represented by the purple and yellow octahedra, and cation intercalation sites are represented by the gray polyhedra. Reprinted with permission from Ref. 2 Copyright 2017 American Chemical Society ...... 15

Figure 6 Schematic of the Jahn-Teller distortion of Mn3+. Two distortions are shown, which slightly alter the energy levels of electrons in the t2g orbital, stabilizing them rather than forcing them to maintain the same energy level. These elongations and compressions cause cyclic stress in the material, leading to structural degradation with extended cycling. Reproduced from Ref. 3 with permission. Copyright 2017 by the Royal Society of Chemistry...... 22

Figure 7 Crystal structure and electrochemical performance of Na0.44MnO2. A) Crystal structure model showing the mobile Na+ in the Na(2) and Na(3) sites. Reproduced with permission from Ref. 102. Copyright 2015 Springer Nature. B) The derivative of the capacity with respect to voltage -1 (dQ dV ) from galvanostatic cycling at 25 mA g-1 in a 1 M Na2SO4 aqueous electrolyte, where each peak denotes a phase transformation. Reproduced with permission from Ref. 84. Copyright 2010 The

Electrochemical Society. C) Capacity retention of a Na0.44MnO2 vs. activated carbon full cell for 1,000 cycles at 5C...... 24

+ Figure 8 Structure of P2-NaxMnO2 where Na occupies two prismatic interlayer sites, MO6 octahedra form edge-sharing layers, and the oxygen stacking sequence is “…ABBA…”...... 26

Chapter 2 Figure 1 Structure of as-synthesized materials: a) schematic illustrating the P2 structure with alternating MO2 (where M is 0.64 Mn and 0.34 Cu or 0.22 Ni and 0.11 Fe, Co, or Cu) layers of edge-sharing octahedra and interlayer Na+. The refined XRD patterns show that each of the four compositions crystallizes into this structure: b) NaNMFe, c) NaNMCo, d) NaNMCu, and e) NaMCu. The colored tick marks show the location of the P2 peaks in each graph. The gray tick marks in e) show the CuO peaks ...... 39

Figure 2 High angle XRD fitting of the Rietveld refinements for: a) NaNMFe, b) NaNMCo, c) NaNMCu, and d) NaMCu and CuO. The tick marks at the bottom of each graph represent the P2 peak locations in each material, while the gray (bottom) tick marks in d) represent CuO...... 40

Figure 3 Scanning electron micrographs of electrodes of each composition of the P2 oxides: a) NaNMFe, b) NaNMCo, c) NaNMCu, and d) NaMCu. The particle size and morphology does not vary with the transition metal composition ...... 41

Figure 4 Structure and composition of an individual particle of NaNMCo:a) HAADF- STEM image showing the layered structure with an average interlayer spacing of 5.8 Å; corresponding EDS elemental mapping of b) Na, c) Ni, d) Mn, e) Co, and f) O; g) composite EDS elemental mapping of Na and Mn, which shows that Na is located between layers of Mn. HAADF-STEM images courtesy of Dr. Rohan Dhall...... 42

Figure 5 Ex situ XRD of the four compositions of P2 oxides after water exposure for 8 days, showing that the NaNMFe and NaNMCo form a birnessite-like phase (♦) in addition to the P2 phase (*). Both NaNMCu and NaMCu retain the P2 phase, indicating improved stability in the presence of water as compared to NaNMFe and NaNMCo ...... 43

Figure 6 STEM images of the layered structure of the four compositions of P2 oxides before (a, c, e, g) and after (b, d, f, h) water exposure (scale bar = 2 nm) indicate that the NaNMFe and NaNMCo experience an increase in interlayer spacing with water exposure along with more interlayer spacing disorder, while NaNMCu and NaMCu retain the same interlayer spacing. HAADF-STEM images courtesy of Dr. Rohan Dhall...... 46

xii

Figure 7 TGA of the pristine powders immediately after removal from the glovebox and of the water-exposed powders after 16 days. The pristine powders (dashed lines) show a small mass loss due to adsorbed water. Both a) NaNMFe and b) NaNMCo show clear steps corresponding to the removal of interlayer water, while c) NaNMCu and d) NaMCu show small steps that can be attributed to water adsorbed onto the surface ...... 48

Figure 8 Electrochemistry of the four compositions of P2 oxides in an aqueous Na+ electrolyte at 0.1 mV s-1: a) NaNMFe exhibits a semi-rectangular CV even in the first cycle, b) NaNMCo exhibits defined redox peaks in the first cycle and an almost rectangular CV in the second, c) NaNMCu retains most of its redox peaks during the second cycle, indicating higher retention of the P2 phase, and d) NaMCu also retains most of its redox peaks and thus the P2 structure. “A.B” represents an acetylene black electrode on Ti mesh; it demonstrates that the measured current is primarily from the redox activity of the transition metal oxide particles in the electrode ...... 50

Figure 9 Ex situ XRD of slurry electrodes before (a) and after (b) electrochemical cycling in 1 M Na2SO4 aqueous electrolyte. a) Before electrochemical cycling, the (002) peak of the P2 phase is at the same position for all compositions indicating similar Na+ content and interlayer spacing. b) After electrochemical cycling, NaNMFe and NaNMCu almost completely transform to a birnessite-like phase. NaNMCu partially transforms, while NaMCu retains the P2 phase and the highest final Na+ content, as indicated by the slightly higher position of the (002) peak at ~ 17 °. .... 52

Figure 10 Effect of the 1 M Na2SO4 electrolyte pH on the electrochemical behavior of NaNMCo: a) First cycle CVs of NaNMCo between 0 – 0.6 V show similar redox peak positions as a function of electrolyte pH, with slightly higher current response at pH 13 due to increased OER activity. b) Ex situ XRD of the electrodes cycled to 0.6 V show the formation of two phases after cycling regardless of pH. Due to the limited Na+ extraction at 0.6 V, the electrodes cycled at each pH only partially transform to the birnessite-like phase ...... 55

Figure 11 a) First cycle CVs of NaNMCo between 0 – 0.8 V at pH 6, 9, and 11, showing similar redox peak positions as a function of pH. b) Ex situ XRD of the electrodes cycled to 0.8 V shows that by cycling to a higher anodic potential, NaNMCo (regardless of electrolyte pH) almost completely transforms into a hydrated birnessite-like phase ...... 56

-1 Figure 12 Electrochemical cycling at 0.5 mV s in 1 M Na2O4 of a) NaNMCo from 0 – 0.8 V, b) NaNMCo from 0 – 1.1 V, c) NaMCu from 0 – 0.8 V, and d) NaMCu from 0 – 1.1 V. Each has an acetylene black (“A.B.”) background at 0.5 mV s-1 for reference ...... 57

-1 Figure 13 Cycling stability of NaNMCo and NaMCu at 0.5 mV s in 1 M Na2SO4 over

xiii

two different potential windows. a) Anodic capacity, b) Coulombic efficiency, and c) ex situ XRD of the electrodes after 50 cycles at 0.5 mV s-1. * indicates the P2 phase, while ♦ indicates the birnessite phase ...... 58

Figure 14 Schematic of the transformation from a P2 oxide to a birnessite-type oxide with Na+ deintercalation in aqueous electrolytes. The electrostatic repulsion between facing oxygen anions increases the interlayer spacing of the P2 oxide with Na+ deintercalation. At a certain amount of Na+ in the interlayer (~ 0.4 Na+ per formula unit), which can be controlled by the transition metal M content and the applied maximum anodic potential Vmax, water is intercalated into the interlayer, transforming the structure to a birnessite-like phase ...... 59

Figure 15 SEM images showing the microstructural effects of water intercalation in P2 oxides. a) Pristine NaNMCo, b) NaNMCo after 50 cycles to 0.8 V, c) NaNMCo after 50 cycles to 1.1 V, d) pristine NaMCu, e) NaMCu after 50 cycles to 0.8 V, and f) NaMCu after 50 cycles to 1.1 V. The water intercalation and transformation to a birnessite phase cause large sections of the particles to delaminate, and even fracture. All materials exhibited an increase in surface roughness with cycling, but NaMCu showed very little exfoliation after cycling to 0.8 V. 100 nm scale bar ...... 60

Figure 16 Scanning electron micrograph of a NaNMCo particle after water exposure ...... 61

Figure 17 Equivalent circuit used for modeling the EIS results ...... 62

Figure 18 EIS results of NaNMCo and NaMCu before and after cycling to 0.8 V for 10 cycles at 0.5 mV s-1. a) Nyquist plot of NaNMCo and b) NaMCu showing a large increase in charge transfer resistance after cycling. Real impedance [Re(z)] vs. ω-1/2 for c) NaNMCo and d) NaMCu before and after cycling, where the slope of the linear region was used in the calculation of the diffusion coefficient ...... 63

Chapter 3 Figure 1 Fabrication of the expansion pouch. (A) Dialysis tubing folded over on itself to form a double-layer wall, with one end folded into a point to thread through the Pt wire coil. (B) The threaded dialysis tubing with parafilm securing the folded end to the Pt wire. (C) After folding the tubing over the Pt wire and filling the pouch with P2 NaMCu powder, parafilm secures the outer wall of the pouch as well ...... 72

Figure 2 The P2 structure of the pristine material, showing the edge-sharing MO6 octahedra forming layers with … ABBA … oxygen stacking, where M represents Mn and other transition metals. The Na+ are located in two types of trigonal prismatic sites between the oxide layers...... 75

xiv

Figure 3 Mechanism of water intercalation into P2-type NaMCu upon electrochemical cycling in 1 M Na2SO4. (A) Cyclic voltammetry at 0.5 mV/s. A.B. indicates “acetylene black,” the electrochemical response of the conductive carbon in the electrode. (B) Cartoon showing the insertion of water molecules (red) from the electrolyte into the material interlayer to compensate for the electrochemical de-intercalation of Na+ (dark blue) ...... 76

Figure 4 Structural changes of P2 NaMCu upon electrochemical cycling (A) Operando synchrotron XRD during the first two CV cycles at 0.5 mV/s. The right-most panel shows the applied potential (dashed line) and the current response (solid line). During the first anodic cycle, the interlayer peak of the hydrated birnessite- like phase (~7 °2θ) emerges around 0.9 V. Both the P2 and the hydrated peak show reversible, continuous changes in the interlayer spacing as a function of potential attributed to Na+ de/intercalation. The peak at 8.1 °2θ is due to the electrochemical cell. (B) XRD pattern of the pristine NaMCu powder (“NaMCu”), where the (002) peak indicates the interlayer spacing. Post- electrochemistry, the NaMCu transforms to a hydrated structure. The substrate peaks of the Ti current collector are indicated by •. In situ XRD image courtesy of Natalie Geise...... 78

Figure 5 Operando synchrotron XRD of NaNMCu, showing the P2 (002) peak ~ 9.11 °2θ, which decreases with material oxidation and Na+ extraction up to 0.8 V, and returns to its original position upon reduction to 0 V. This material also experiences the emergence of the hydrated phase at ~ 7.23 °2θ, which continuously contracts (expands) during reduction (oxidation) due to interlayer cation intercalation (deintercalation). Both phases remain electrochemically active during the second cycle, showing reversible interlayer spacing changes. In situ XRD image courtesy of Natalie Geise...... 80

Figure 6 Effect of batch expansion on particle morphology: (A) a pristine P2 NaMCu particle has a compact structure, which expands after electrochemical water insertion. (B) A schematic of the electrochemical expansion setup, where the P2 material is contained in a dialysis tubing pouch around a coil of Pt wire, and the counter electrode is Ni foam. (C) A typical fully expanded NaMCu particle, which retains its ab-plane morphology but expands vertically due to water insertion. Scale bar 2 μm...... 81

Figure 7 Chronoamperometric expansion of the fully (dark green; F.E.) and partially (light green; P.E.) expanded materials. The “noise” of each curve could be related to the electronic contact of particles within the pouch that determines the extent of electrochemical expansion ...... 82

Figure 8 Structural characterization of expanded NaMCu materials. (A) Powder XRD shows the complete transformation of the F.E. material into the hydrated phase, while the P.E. material contains both the hydrated phase and residual P2 phase. (B) TGA shows that both F.E. and P.E. NaMCu materials lose a significant

amount of water with increasing temperature. SEM of the (C) pristine NaMCu powder and (D) F.E. NaMCu powder shows that the expanded particles retain their initial hexagonal morphology and particle size but are now expanded along the layers. Scale bar 3 µm ...... 83

Figure 9 CVs of the pristine P2, P.E., and F.E. NaMCu materials in 0.5 M K2SO4 electrolyte at (A) 1 mV/s, (B) 10 mV/s, and (C) 100 mV/s. The specific current from just the acetylene black (A.B.) conductive additive is shown for reference.... 86

Figure 10 Cyclic voltammograms of the first cycle of pristine NaMCu mesh electrodes in Na2SO4 (dotted line) and K2SO4 (solid line) aqueous electrolytes at 0.1 mV/s. Here, the two primary redox peaks of NaMCu in Na2SO4 occur before 0.8 V vs. Ag/AgCl. Since the hydrated phase in Figure 4 appears around 0.9 V, this suggests that completion of the redox reactions associated with the two anodic redox peaks leads to water intercalation and subsequent material expansion ...... 86

Figure 11 Electrochemical energy storage rate capability and post-electrochemical cycling material structure. (A) Cathodic capacitance and (B) rate capability (cathodic capacitance normalized to the capacitance at 0.1 mV/s), from 0.1 to 100 mV/s. The low capacity and rate capability of the acetylene black (A.B.) conductive additive shows that the capacitive electrochemical response is due to the oxide active materials. (C) Ex situ XRD of electrodes after electrochemical cycling shows that the F.E. and P.E. retain their initial structures ...... 88

Figure 12 (A) Cycling stability of F.E., P.E., and P2 NaMCu over 600 cycles at 10 mV/s. (B) Ex situ XRD after 600 cycles shows that the F.E. NaMCu retains the hydrated phase, while some of the remaining P2 material in the P.E. NaMCu electrode expanded after prolonged cycling ...... 89

Figure 13 SEM images of (A-B) F.E., (C-D) P.E., and (E-F) P2 NaMCu electrodes after 600 cycles in 0.5 M K2SO4. While most F.E. particles show expansion or a surface coating, few P.E. particles show surface coating, and few P2 particles even show expansion. Scale bar 500 nm ...... 91

Figure 14 CV comparison of P.E. NaMCu and activated carbon (A.C.) on the basis of their specific current at (A) 1 mV/s, (B) 10 mV/s, and (C) 100 mV/s. At sweep rates up to ~ 20 mV/s, the P.E. NaMCu out-performs the activated carbon, although both electrodes appear relatively resistive at 100 mV/s ...... 93

Figure 15 (A) Volumetric capacity/capacitance and (B) rate capability of P.E. NaMCu and activated carbon (A.C.) electrodes ...... 93

xvi

Chapter 4 Figure 1 Schematic of the proposed energy storage mechanism of A) the nanostructured birnessite, showing with B) surface or C) interlayer processes ...... 102

Figure 2 A typical electrodeposition curve from the EQCM, showing the chronoamperometic curve (black) and linear mass change (blue) ...... 104

Figure 3 Data from the EQCM calibration in 0.5 M HNO3 and 50 mM AgNO3. A) The frequency change during Ag deposition, showing a simple linear process. B) Calculated values of Cf at each current density, which were then averaged to obtain the experimental Cf ...... 108

Figure 4 Structure and morphology of electrodeposited birnessite thin films. A) Model of the birnessite crystal structure, showing interlayer K+ (purple) and water (grey) species. B) XRD pattern showing the interlayer spacing peaks; reference peaks are from PDF 00-042-1317. C) Raman spectrum showing the basal plane (ν2) and out-of-plane (ν1) Mn – O bond stretching modes. D) SEM image of large “islands” that form at the bottom of an electrode furthest away from electrical contact. E) Higher magnification SEM image of birnessite nanosheets showing the tissue-like morphology. F) AFM liquid AC tapping mode image in 0.5 M K2SO4 electrolyte showing the “island” morphology is preserved upon immersion into a liquid. The white squares show the locations of the two points measured in Section 4.3.2 ...... 111

Figure 5 Film thickness calculated from A-C) SEM cross-sections and D) corroborated with AFM cross-sections. The SEM gives an average film thickness of 1.47 ±0.78 μm, and the AFM height trace across one of the islands shows an overall film thickness of 1-2 μm (1.4 μm in the spot shown), with raised edges and flatter island centers ...... 112

Figure 6 Electrochemical performance of birnessite MnO2 in 0.5 M K2SO4 (black) -1 and Li2SO4 (green, dashed). A) CV at 10 mV s showing a quasi-rectangular shape. B) Capacitance (and capacity) as a function of scan rate, showing 71% capacity retention from 5 to 200 mV s-1 and that at this film thickness, the behavior of birnessite is the same in both electrolytes ...... 113

Figure 7 Ex situ XRD of birnessite. A) The full patterns taken on the electrode cycled in K2SO4 show no shift of the Au substrate peak, while B) the normalized (001) peak shows interlayer expansion. The same is observed in Li2SO4, where C) shows the full patterns and D) shows the normalized (001) peak ...... 115

Figure 8 Mass changes vs. potential of birnessite MnO2 in A) K2SO4 and B) Li2SO4. The mass change in K2SO4 is only ~twice that of the change in Li2SO4, indicating that bare ions as not the only involved species—if they were, the mass changes would be 9.6 μg in K2SO4 (atomic mass of K = 39 g/mol) and 1.7 μg in Li2SO4. This, in addition to the MCR values, indicate that multiple

xvii

species are involved in the charge storage. However, the relatively constant mass change in both electrolytes does indicate that even if there are multiple mechanisms involved, they do not differ much from each other ...... 116

Figure 9 Plots of Potential and Mass vs. Charge for A) K2SO4 and B) Li2SO4. There are 3 distinct sections in K2SO4, and 5 (two anodic, and 3 cathodic) in Li2SO4. These indicate that there may be multiple processes involved in the charge storage mechanism of birnessite MnO2 ...... 117

Figure 10 Cumulative fit curves of the in situ Raman spectra of birnessite during aqueous electrochemistry in A) K2SO4 and B) Li2SO4. The spectra show an increase in Raman shift of the ν1 peak, and a relatively stable ν2 peak...... 118

Figure 11 Deformation of birnessite in A) K2SO4 and B) Li2SO4. The deformation curves of birnessite at 10 and 50 mV/s in K2SO4 almost entirely overlap, indicating the same charge storage mechanisms at both rates. The noisy deformation signal in Li2SO4 is due to poor contact of the AFM tip with the electrode during cycling ...... 123

Figure 12 Multi-modal characterization of birnessite MnO2 in K2SO4 (left) and Li2SO4 (right), showing the results of each technique as a function of potential. A,B) Ex situ XRD shows reversible changes in interlayer spacing. C) gCV in 0.5 M K2SO4 at 10 mV/s shows that the current is directly related to mass changes, while in D) Li2SO4, the EQCM is more sensitive than the electrochemical signal. E,F) Shift of the Raman ν1 peak corroborates the interlayer spacing change shown finrom XRD. G, H) CVs and mCVs at 50 mV/s from operando AFM dilatometry show that multiple processes occur during electrochemical cycling that combined lead to the CVs ...... 126

Figure 13 Rate behavior of birnessite. Deformation from 50 – 200 mV/s in A) K2SO4 and B) Li2SO4, Difficulty maintaining contact during AFM dilatometry led to increased hysteresis in the data at 50 mV/s in Li2SO4. The mass change from 20 – 200 mV/s in C) K2SO4 and D) Li2SO4. The films behave similarly in both electrolytes, with little visible hysteresis until 200 mV/s ...... 127

Figure 14 MCRs as a function of sweep rate in A) K2SO4, and C) Li2SO4. In K2SO4, MCRs slowly increase with sweep rate. If the species involved as the electrolyte cation and free waters, as we expect, in K2SO4 this may indicate that there is less opposing H2O flux with increasing sweep rates. In Li2SO4 the first segment during each potential sweep quickly decreases with sweep rate, while the later segments slowly increase. This suggests that fewer waters are also involved with increasing rate in Li2SO4. ‘a’ denotes anodic, and ‘c’ denotes cathodic ...... 128

Figure 15 Electrochemomechanical and gravimetric behavior of birnessite as a function of rate. The CVs from the operando AFM cell in A) K2SO4 and B) Li2SO4 show

xviii

some polarization but maintain their shape from 50 to 200 mV s-1. The mCVs in C) K2SO4 show two clear sets of peaks, while in D) Li2SO4 the mechanical behavior mirrors the CV. Finally, CVs and gCVs in E) K2SO4 match, while in F) Li2SO4 the gCV peak is polarized beyond the CV peak at high rates ...... 130

Appendix A Figure 1 Color of solution after hydrothermal synthesis of birnessite. A) The dark turquoise Mn5+ solution in a centrifuge tube, and B) the same solution at a later step in the rinsing process, when it had been slightly diluted ...... 170

Figure 2 SEM of the crystalline birnessite particles. Scale bar 1 μm...... 171

Figure 3 Raman spectra of crystalline birnessite particles A) using a slightly higher power, which evolved a spinel component in the peak ~655, and B) a lower power which focused on the lower angle peaks. Both of these are significantly clearer than the Raman spectra discussed in Chapter 4, and show many peaks not commonly associated with birnessite ...... 172

Figure 4 XRD of the crystalline birnessite particles, which match PDF 00-042-1317 ...... 172

Figure 5 Electrochemistry at 5 mV/s in 1 M Na2SO4 of birnessite dropcast onto glassy carbon (GC) and heated at 60 °C. Kevin Matthews prepared this electrode and took this scan ...... 173

Figure 6 AFM topography image of crystalline birnessite taken in water at NC State ...... 174

Appendix B Figure 1 Baseline to be subtracted from filtered deformation data...... 181

Figure 2 Baseline-subtracted deformation data (nm) vs. time (s)...... 182

Figure 3 Baseline-subtracted deformation data vs. potential. The legend shows the active material, sweep rate (in mV/s), and filter values—although DF has not yet been applied...... 182

Figure 4 The negative deformation rate as a function of time, showing the filtered data in the orange line. Filtering and outlier removal are important for removing sudden discontinuities from this noisy data ...... 183

Figure 5 Deformation rate and current vs. potential. This shows how the AFM data gives similar results to the current, which is discussed more in Chapter 4...... 183

Figure 6 Baseline subtraction in the EQCM code ...... 194

Figure 7 Various potential equations for two-species redox reactions occurring in birnessite MnO2 upon electrochemistry in a K2SO4 electrolyte ...... 204

xix

Figure 8 Example results of the EQCM film discussed in Chapter 4 at 5 mV/s, for an MCR of 29.2 g/mol e- ...... 205

Appendix C Figure 1 Baseline mode settings for background subtraction. Baseline Mode: user defined. Baseline analysis points: 1st and 2nd derivative zeros. Smoothing window size: 30. Polynomial order: 4. Threshold: 0.05. Points: 4...... 212

Figure 2 Baseline points not in the dataset baseline. The third point needs to be moved .... 213

Figure 3 Settings for baseline creation. Connect points by interpolation, keep the number of baseline points the same as the input data, and use a spline for the interpolation method ...... 214

Figure 4 Example curve heading after baseline subtraction ...... 214

Figure 5 An example of where to select the peaks ...... 215

Figure 6 The NLFit dialog. Use the circled “1 iteration” button and make minor adjustments as needed to peak width and center until the peaks stop moving much ...... 216

Figure 7 Calculated parameters from the peak fitting ...... 217

Figure 8 Final Origin worksheet with the calculated data ...... 217

Figure 9 Comparing the raw Raman data with the cumulative fit peak at each potential .... 218

Figure 10 Normalized cumulative fit Raman spectra for the whole cycle...... 219

Figure 11 Calculated Raman peak center graph ...... 219

Figure 12 Full XRD pattern of the birnessite electrodes ...... 220

Figure 13 Zoomed-in XRD showing the (001) peak of the birnessite ...... 221

Appendix D Figure 1 EQCM behavior of a thick film in K2SO4 at 10 mV/s. A) The CV looks like a typical birnessite film, while the mass change shows regions of mass loss and gain. B) The gCV shows no clear relation to the CV, indicating that the mass changes may not be directly related to electrochemical events ...... 224

Figure 2 Potential and mass vs. charge of a thick film in K2SO4 at 10 mV/s...... 225

Figure 3 Potential solutions for the region of charge storage in a thick birnessite film

where the MCR equals -14.8 g/mol e- during the anodic cycle...... 225

Figure 4 gCVs at 50 mV/s in K2SO4 of A) the gold EQCM crystal, B) the 0.024 mg birnessite film, C) the 0.18 mg birnessite film, and D) the 0.68 mg birnessite film...... 228

xxi

CHAPTER 1

Motivation and Introduction

1.0 Introduction

The beauty of materials science and engineering is its ability to attribute observable phenomena to atomistic behavior in solids. It makes the infrastructure we use in our daily lives more understandable and gives us the keys to improve it. In a society that relies heavily on on- demand energy, using materials science to improve energy storage devices is vital to technological and societal advancement. In 2017, renewable sources generated 17% of energy in the United

States, with 8.8 % produced by intermittent wind and solar.4 Electrochemical energy storage (EES) devices are especially promising for microgrids and storing intermittently generated energy due to their high efficiency and versability. Unfortunately, the EES devices such as rechargeable

(secondary) batteries used to store and dispense the collected power remain expensive, inefficient, and/or hazardous. Thus far, the most promising have been derivatives of well-developed high- performance lithium-ion battery chemistries for electric vehicles and personal electronics. These systems use flammable electrolytes and rare transition metals, making them too risky and expensive at the scale required for grid storage, where the system safety and abundance of the components is even more important than for portable electronics.5 Significant advances in device lifetime, power capability, and safety are required to support a continued increase in renewable energy use.

In my dissertation, I addressed the need for advanced EES technology by studying the fundamental charge-storage mechanisms of manganese-based layered oxides in aqueous electrolytes. The 2017 “Next Generation Electrical Energy Storage” Basic Science Needs (BSN) report highlights the need to “tune functionality of materials and chemistries to enable holistic

design for energy storage”.5 That is, understanding and altering the interactions between the key components of a battery to improve its performance. These components are the electrodes, which store charge, and the electrolyte, which conducts ions between electrodes. The electrodes are connected by an external circuit to enable curresponding electron transfer upon ion movement.

Safe and efficient electrolytes are necessary for grid-scale EES, and neutral-pH aqueous electrolytes offer significant safety advantages over existing non-aqueous and extreme-pH aqueous systems technology due to their inflammability and relatively low corrosivity. However, the interactions between water, electrolyte ions, and the electrode materials are complex and are not yet fully understood, especially for secondary battery systems. Furthermore, understanding derived from this research is applicable to emerging aqueous technologies that require ion intercalation into host materials such as electrochemical desalination and element recovery. This dissertation research focuses on manganese-based layered oxides for aqueous intercalation cathodes. Other classes of materials studied for aqueous intercalation include the low conductivity polyanionic phosphates and Prussian blue analogues. While NaTi2(PO4)3 is the most common aqueous Na+ anode,6–9 phosphate cathode materials have low conductivity, low water-stability

-1 10 (Na3V2(PO4)3), and low theoretical capacity (~ 62.5 mAh g for Na2VTi(PO4)3). Prussian blue analogues have low voltages and a similar capacity limit, although these are improving.11 On the other hand, manganese-based oxides have higher redox potentials, theoretical capacities, and stability. Manganese is attractive for large scale applications because of its abundance.12,13 As a 3d transition metal, it is redox-active, relatively light-weight, and forms a wide range of structures capable of intercalating a variety of cations, including H+, Li+, Na+, K+, Mg2+, and Zn2+.13–16

Among the many polymorphs, the layered structures in particular offer capacity > 100 mAh/g,17

and an interlayer environment which can be readily tuned by transition metal chemistry and interlayer water and cation content.18–20

By investigating how the atomic structure of manganese-based layered oxides in aqueous electrolytes affects their electrochemical energy storage behavior, my research addresses the need for holistic design of materials for aqueous batteries with promising economic, environmental, and safety profiles. In the remainder of this introduction, I will set the stage by further introducing fundamentals of aqueous electrolytes, electrochemical charge storage reactions, and a variety of manganese-based oxides.

1.1 Energy Storage Mechanisms

Electrochemical energy is typically stored using two types of electrochemical reactions: faradaic and non-faradaic.21 In faradaic processes, electron transfer to or from the species of interest reduces or oxidizes it, respectively. These reactions are also called “charge transfer” or

“redox” reactions. Transition metal oxides can undergo conversion reactions, surface redox, or insertion redox reactions. Surface and insertion reactions exhibit higher reversibility and rate capability because they involve significantly less structural rearrangement than conversion reactions. Because of this, the remainder of my dissertation focuses on the former. For surface redox and ion insertion reactions in transition metal oxides, these faradaic reactions involve electrons transferred via the external circuit coupled with ions transfered from the electrolyte to maintain charge neutrality of the electrode material. This typically involves electron transfer to and from the valence electron orbitals, which can be filled and emptied without forming and breaking primary bonds already within the structure.22 In its simplest form, faradaic reactions are often considered to follow the Nernst equation:

푅푇 [푅] 퐸 = 퐸0′ + 푙푛 푛퐹 [푂푥]

Where:

E = the potential at which the reaction occurs

E0′ = the standard reaction potential

R = the universal gas constant, 8.314 J/K mol

T= temperature in Kelvins

n = number of e- transferred in the reaction

F = Faraday’s number, 96485 C/mol e-

[Red] = concentration of reduced species

[Ox] = concentration of oxidized species

This equation can be expanded with terms to account for species interaction, electron or ion migration, availability of reactants, and type of reaction products.21 It gives rise to a single peak as in Figure 1A, and produces large capacities on the order of ~180 mAh/g for a single-

23 electron reaction in MnO2. However, practical capacities may be lower as most reversible ion insertion reactions in aqueous electrolytes only transfer 0.1-0.5 e- per transition metal center.

Insertion-based faradaic reactions involve the bulk of the electrode material requiring fast solid state ion transport and electron transport. Since few materials exhibit both simultaneously, electrode architectures are carefully engineered to enable fast ion and electron diffusion. The electron transfer in faradaic processes leads to changes in bond lengths and energies observable by

X-ray diffraction (XRD), and vibrational spectroscopy such as infrared (IR) and Raman. This is coupled with signature (primarily) monotonic mass and volume changes.24–31 From a fundamental standpoint, the changes in bond length and structure due to faradaic processes can limit material

rate capability and cyclability. Typical rechargeable faradaic systems store charge on the order of hours, and have lifetimes of ~1000 cycles.32

Non-faradaic reactions, on the other hand, involve charge accumulation at the electrode- electrolyte interface via polarization of the delocalized conduction band electrons without electron transfer.21,22 The charge on the electrode causes the formation of the electric double layer (EDL) on the electrolyte side, which will be described more in Section 1.2. These reactions are also called

“capacitive”, and their charge is determined by:

푞 휀 휀 퐴 퐶 = = 푟 0 퐸 푑

Where:

C= capacitance (F)

Q = charge on the electrode

E = potential window over which the electrode is cycled

εr = dielectric constant of the electrolyte

ε0 = dielectric constant of a vacuum

A = surface area of the electrode

d = double layer or charge separation distance

The double-layer capacitance is typically on the order of 4-20 μF/cm2 of the electrode material surface area,22,33,34 but EDL capacitors are able to attain high capacitance values up to 100

– 300 F/g (28 – 83 mAh/g over 1 V) because of the large surface area of activated carbons (>1000-

2000 m2/g) and the small distance at which ions can approach in aqueous electrolytes.22,33,35 Figure

1B shows the typical rectangular CV of a capacitive non-faradaic reaction, which exhibits no redox

peaks. Capacitive reactions store energy on the order of seconds, with lifetimes of ~ 1,000,000 cycles.22,36

Figure 1. Characteristic cyclic voltammetry response of an A) Nernstian faradaic redox couple showing reversible peaks and low background current in regions away from the redox peak. B) A non-faradaic EDL capacitance response showing a constant current across the potential window.

While pure Nernstian reactions are easily distinguished from pure EDL behavior, not all energy storage materials fit into these neat boxes. In particular, some faradaic reactions occur with high degrees of reversibility at charge times from tens of seconds to tens of minutes. These fast, highly reversible redox reactions that exhibit a continuous dependence of faradaic charge on the electrode potential and occur at or near the material surface are called “pseudocapacitive”.37,38

Given the respective limitations of faradaic batteries and EDL capacitors, the prospect of energy storage devices capable of bridging the gap in their performance by storing relatively large amounts of charge quickly and with extended cyclability is highly attractive. However, pseudocapacitance has been widely debated since its conceptualization, as extensively discussed

in a recent review paper.39 Initially used to describe fast, faradaic reactions such as the heterogeneous under-potential deposition of a single layer of metal atoms, “pseudocapacitance” was not intended to describe a particular reaction mechanism. The only limitations were that the reaction 1) could not be limited by solid-state diffusion for charge times in the order of minutes, and 2) was highly reversible and could not be attributed to EDL formation. When it was first proposed, intercalation chemistry had not yet been established, and typical redox-active energy storage reactions were kinetically-limited alloying and conversion reactions. In 1971 Trasatti et al. found that hydrous RuO2 exhibited pseudocapacitive behavior, the first demonstration in transition metal oxides.40 Since then, the energy storage community has devoted itself to understanding what materials design mechanisms lead to pseudocapacitance.

The current working definition requires that the electrodes in question must exhibit almost purely capacitive CVs, while storing energy on the same order of magnitude as faradaic materials.41 However, this does not account for the redox peaks observed in CVs of many materials which otherwise appear pseudocapacitive, or the fact that almost any material can appear pseudocapacitive if it its particle size is reduced to be on the same order as the diffusion length within the particle.42–44 The broad redox peaks in pseudocapacitive CVs of nanostructured materials such as LiCoO2 and V2O5 are attributed to the distribution of intercalation site energies due to the high surface area, and their rate capability to the short diffusion lengths.42,43 In micron- scale particles, these materials clearly behave as Nernstian faradaic materials. This highlights the need to understand what mechanisms give rise to pseudocapacitance, so that intrinsically pseudocapacitive materials can be engineered and implemented.

1.2 Aqueous Electrolytes

The interactions between water and transition metal oxide electrodes are similar to those that occur during geological weathering. In EES, water is a unique electrolyte solvent because its high polarity and small molecular size allow it to strongly solvate salts, spontaneously hydrate and corrode oxide surfaces, and form a highly conductive, structured electrolyte.1,45,46 Aqueous electrolytes have a conductivity of 10-190 mS cm-1 vs. <10 mS cm-1 for most non-aqueous electrolytes, making them attractive for high-power systems.8,47

Water molecules readily react with under-coordinated metal cations and oxygens exposed on pristine oxide surfaces.48 In some oxides, this enables the formation of hydroxide surface phases via hydrolysis reactions.49 Although water molecules frequently exchange between the surface and bulk electrolyte, the organization of aqueous electrolytes at an electrode surface is typically described using static models. Most build off the limiting cases of the simple Gouy-Chapman-

Stern model (Fig. 2A).50 Here, adsorbed water molecules form the Inner Helmholtz Plane, while hydrated cations form the Outer Helmholtz Plane. The width of the parallel-plate capacitor formed by these two planes is called the Stern layer.51 The Stern layer narrows with increasing salt concentration, increasing the EDL capacitance.51 Electrode polarization during electrochemical cycling increases interfacial charge and therefore further increases EDL capacitance.

Unfortunately, the uniqueness of water also leads to practical difficulties in implementing aqueous electrolytes. Thermodynamically, water can only withstand an applied potential of 1.23

V without undergoing degradation reactions to evolve oxygen or hydrogen gas.52,53 This significantly limits the capacity and energy density available in aqueous EES relative to non- aqueous electrolytes with ~ 4 V thermodynamic stability windows, as energy density is directly proportional to the applied voltage.32,54 In addition, non-aqueous electrolytes are kinetically

stabilized by electrolyte degradation at the electrode-electrolyte interface to form a stable, ionically conductive, and electronically insulating cathode- or solid-electrolyte-interphase (CEI or SEI) layer.55,56 Because the decomposition products of water are volatile gases or reactive ions,52,53 an

SEI-like protective film cannot readily form in aqueous electrolytes. Figure 2B shows a Pourbaix diagram for water, which describes the thermodynamic stability of water as a function of both pH and applied potential.57 In water, the oxygen evolution reaction (OER) occurs above the maximum positive (anodic) potential, and the hydrogen evolution reaction (HER) occurs below the minimum

(cathodic) potential. When these reactions occur, they lower electrode stability by altering the local pH at the electrode interface.6,58,59 If charge transfer to the electrode causes the material to reach a soluble valence state, the electrode material may dissolve.8,60 In the last several years, researchers have determined that the formation of a protective SEI-like layer may be possible in “water in salt electrolytes” (WiSE), which are more salt than water by both mass and volume.52 These electrolytes are stable up to ~ 3 V because fewer water molecules are available to interact with the electrode surface, allowing significantly less active material dissolution during cycling.1,8,52,61–65

Because they offer a wider potential stability window and are less corrosive than aqueous electrolytes, while maintaining the desirable inflammability, WiSEs may be of interest for follow- up studies to those presented in this dissertation.

In addition to WiSE, other approaches to improving the stability of oxides in aqueous Na+ electrolytes by removing the driving force for water molecules to undergo decomposition reactions at the electrode surface include: (1) removing dissolved oxygen,65–67 (2) introducing an electrolyte additive or electrode surface coating that conducts ions but prevents water molecules from

59,67–69 contacting the active material. Dissolved O2 and CO2 can be removed from the electrolyte

9,65–67,70,71 by bubbling N2 and Ar into the cell before electrochemical characterization. Most studies

demonstrate mild improvements in the short-term cycling stability and Coulombic efficiency,8,66,70 but long term cycling still shows a severe drop in performance, indicating that removal of excess oxygen from the electrolytes does not completely address the challenges of electrochemical energy storage in aqueous electrolytes.9,70 Electrolyte additives such as disodium propane-1,3-disulfonate

(PDSS) and sodium dodecyl sulfate allow higher cyclability than deaerated electrolytes.59,67 They also offer a cheaper alternative to the water-in-salt electrolytes, although they do not reach as high of anodic potentials.

Figure 2. A) Gouy-Chapman-Stern model of the electric double layer at a transition metal oxide/aqueous electrolyte interface. The electrochemical potential at the electrode-electrolyte interface decreases linearly across the Stern layer thickness (dStern), where the coordinated waters of the Inner Helmholtz Plane (IHP) and hydrated cations of the Outer Helmholtz Plane (OHP) form a structured layer of water at the interface. B) Reactivity of water demonstrated by a Pourbaix

(potential vs. pH) diagram of water showing the thermodynamically stable region. The upper (red) dashed line represents the OER, and the lower (blue) dashed line shows the HER. Reproduced from Ref. 1 by permission of The Royal Society of Chemistry.

The high polarity of water enables reactions between water molecules and under- coordinated metal cations and oxygens on the electrode surface.48 These reactions are enhanced

+ - by the auto-dissociation of water into the reactive H3O and OH species, which increases the likelihood of electrode material degradation relative to non-aqueous electrolytes since many oxides will readily undergo hydrolysis upon protonation.49 Figure 3 is a schematic of how the aqueous electrolyte interacts with the electrode, hydrating it, co-intercalating with the cations,72 and coordinating to the surface, which lead to gas evolution at the right applied potentials.49

Figure 3. Strong interactions of aqueous electrolytes with a hydrated layered transition metal oxide, including surface coordination and hydration by free waters.

One important signature of aqueous electrolytes is the effect of water’s polarity on diffusion of cations in solution. Aqueous electrolytes form short-range hydrogen-bonded ordered network of tetrahedrally-coordinated water molecules.45,73,74 Within this network, anions similar to O2- occupy water sites and interact with water via H-bonds, while metal cations are fully coordinated by water molecules.73 The ionic strength, or point charge density, of cations determines the size of their solvation shell.75 For the monovalent cation electrolytes I studied, the

hydrated radius of the cations is inversely proportional to the crystal size, shown by the comparison of their the crystal, hydrated, and Stokes radii in Table I. The Stokes radius is experimentally calculated from the equivalent conductance of the relevant hydrated species.75 For example, although the small size of unsolvated Li+ lends itself to fast solid-state diffusion within electrode materials, in aqueous electrolytes its high charge density results in larger Stokes and hydrated radii, indicating the slower diffusion of Li+ through aqueous electrolytes.15,29,76–78 In carbons, the high charge density of Li+ results in slightly lower capacitance because the larger solvation shell means

Li+ are 1) slightly further from the electrode surface than other cations, 2) the areal density of Li+ is lower, and 3) solvated Li+ requires larger pores than solvated Na+ or K+.76,79 In Mn-based oxide electrodes, the high charge density of Li+ leads to lower cyclability and rate capability than those observed in K+ electrolytes.15,29,77,78 As K+ has the smallest charge density of these ions, it forms the smallest hydration shell and therefore has faster adsorption/desorption kinetics.80 K+ also interacts less strongly with the electrode material, causing less stress upon (de)intercalation.81,82

For these reason, many manganese-based oxides are studied in K+-containing aqueous electrolytes.15,29,77,78

Figure 4 summarizes the various challenges of working with aqueous electrolytes, highlighting that the goal is safe and economical EES. Materials that are suitable for aqueous secondary batteries are also viable options for redox-active water desalination, or ion separation and element recovery.83–87 The next section will describe some of the manganese-based oxides used in aqueous EES.

Table I. Radii of Alkali Cations in Aqueous Electrolytes. Values from Ref. 75

Ion Ionic Radius (Å) Stokes Radius (Å) Hydrated Radius (Å)

H+ -- (0.28)* (2.82)*

Li+ 0.60 2.38 3.82

Na+ 0.95 1.84 3.58

K+ 1.33 1.25 3.31

*extrapolated from theoretical model

Figure 4. The challenges and prospects of aqueous electrolytes for EES devices. If the hurdles of gas evolution, low voltage, and material dissolution can be overcome, low cost, high power, and sustainable EES awaits. Reproduced from Ref. 1 by permission of The Royal Society of Chemistry.

1.3 Manganese Oxides

1.3.1 Manganese Dioxide

Manganese is the 10th most abundant element in the earth’s crust, and its natural occurrence as Mn2+, Mn3+, and Mn4+, allows it to form > 30 oxide and hydroxide structures, many of which act as heavy metal sorbents in soil and water.13 Of these, the mixed-valence manganese dioxide structures are some of the most heavily-studied materials for EES. The various manganese dioxide polymorphs shown in Figure 5 occur due to variations in polymerization of MnO6 octahedra, and are described by the subsequent octahedral arrangement into tunnels or layers.13,88,89 Within a

14 MnO2 crystal, one octahedron has an edge length of 2.6 Å. For example, α-MnO2 (hollandite, or cryptomelane for K+-containing compositions) consists of 2x2 tunnels which measure ~ 4.6 x 4.6

Å, while layered δ-MnO2 (birnessite) consists of 2D layers of edge-sharing MnO6 octahedra stacked on hexagonal arrays of water molecules and cations, which leads to a 7 Å interlayer spacing.14,90

MnO2 can easily be tuned to form different structures by varying the size of the incorporated alkali or alkaline earth cation, and the amount of structural water,2,91,92 which depend on synthesis pH, solution concentration, and/or heat treatment.14,93,94 Layered and 2x2 tunnel-

+ + + + 2+ + structured MnO2 include additional cations A (where A is Na , K , Mg , Rb . etc.) to balance

2,91,92 + the charges and stabilize the structure. A low pH weakens A -H2O bonds within the layered

91 birnessite structure, squeezing out H2O as the small 1x1 tunnels of β-MnO2 (pyrolusite) form.

+ The A -H2O interaction strengthens at high pH, forming MnO2 structures with larger tunnels such

91 as hollandite (2x2 tunnels) and todokorite (3x3 tunnels). MnO2 can also be electrodeposited to form both the birnessite and intergrowth phases, and the electrodeposition salts and applied potential determine the structure.92

Figure 5. Common polymorphs of MnO2, where MnO6 octahedra are represented by the purple and yellow octahedra, and cation intercalation sites are represented by the gray polyhedra.

Chemical Society.

Only MnO2 polymorphs with insertion sites larger than a single octahedron can accommodate alkali cations, as predicted by the Stokes radii in Table I.14,88 Devaraj et al. compared the α-, β-, γ-, δ-, and λ-MnO2 structures in Na2SO4 and found that only the α- and δ-MnO2 allowed significant Na+ intercalation. The capacity decreased with interior site size: α ≈ δ > γ > λ > β, from

88 297 to 9 F/g. Similar studies in 0.5 M K2SO4 by Ghodbane et al. showed that structures with tunnel (or layer) dimensions < one MnO6 octahedron only gave rectangular (supposedly

pseudocapacitive) responses, likely attributable to only surface redox or H+ insertion. Again, the phases with larger interstitial sites exhibited higher capacity, with the exception of the 3 x 3 tunnel

+ 14 Ni-todokorite, where Ni within the tunnels interfered with cation intercalation. The remainder of this section will describe the behavior of selected MnO2 and manganese-based oxides relevant to this dissertation research.

1.3.1.1 Amorphous MnO2

The pseudocapacitive behavior of amorphous MnO2 in aqueous electrolytes was first reported by Lee and Goodenough in 1999.80 The capacitive behavior is shown by the rectangular

CVs, fast switching times, and is called pseudocapacitive because the amount of charge stored is larger than expected for a purely surface-adsorption process, suggesting that fast redox reactions

95 are also occurring. However, surface-dominant charge storage behavior of amorphous MnO2 leads to swift capacity decline with increasing electrode thickness, making this material impractical from a device standpoint.96

1.3.1.2 Hollandite (2x2) Tunneled α-MnO2

As mentioned above, this phase reversibly intercalates cations into its 2 x 2 (~4.6 Å) tunnels and Mn vacancies for battery-type and redox-active desalination applications.81,88 It has been studied for hybrid EES devices because of its pseudocapacitive behavior,97 which is due to both

H+ and A+ contributions (A+ = Li+, Na+, or K+).81 In particular, K+ is more favorable than Li+ because its large size allows it to interact with several inter-tunnel oxygens at once.98 Although

Mn dissolution leads to low capacity retention when α-MnO2 is cycled below 0 V vs. Ag/AgCl, it has moderate capacity retention of 75% after 500 cycles at 0.5 mA/cm2 between 0 – 1 V.88,99 Over

this potential window in 0.1 M Na2SO4, α-MnO2 exhibits 50 F/g (16 mAh/g) to 240 F/g (67 mAh/g) depending on morphology.88 Young et al. propose that this high capacity is due to the stabilization of conduction band orbitals as cations intercalate: the overlap of the material’s indirect band gap and the stability window of the electrolyte allows cations from the electrolyte to interact with the electrode and form defect sites in the band gap.81,98,100 In later work, they suggest that while the capacity of α-MnO2 is primarily due to faradaic reactions, the high rate capability is due to the stability of A+ “defects” within the structure even after their corresponding e- have been removed.

Because of this, they argue that some cations remain upon oxidation, reducing the number of diffusing ions and leading to high rate capability.

1.3.1.3 Spinel λ-MnO2

This phase of MnO2 is a cubic spinel prepared by chemically or electrochemically

88,101 + delithiating LiMn2O4. Oxidation in aqueous electrolytes containing cations larger than Li

+ + (Na , Mg ) drives a phase transformation to the birnessite δ-MnO2 as water is chemically intercalated to compensate for charge lost during oxidation.102,103 Typically, this material appears capacitive in neutral pH aqueous electrolytes, but becomes visibly redox active in buffered or acidic electrolytes due to the dissolution/solidification process enabled by the higher H+ concentration and an extended potential window.23 It does allow Li+ insertion from aqueous electrolytes, where its band gap sits nicely over the potential window of water, and the pseudocapacitive nature of the charge storage is attributed to the gradual stabilization of individual

Mn – O orbitals just below the conduction band.98 Because the overlapping band gap and stability window of water, charge transfer can readily take place. This explains why the spinel phase

81,102,103 transforms to birnessite rather than remaining inactive like β-MnO2. In the right electrolyte,

this phase exhibits ~100% capacity retention in aqueous electrolytes after 500 cycles from 0 – 1 V vs SCE at 0.5 mA/cm2.88 Because of its cyclability, low cost, and relatively high capacity (up to

360 F/g or 100 mAh/g), Whitacre et al. studied the spinel phase for large-scale (>30 Wh) aqueous batteries. The λ-MnO2 synthesized for these large-scale batteries delivered ~78 mAh/g over a 1.8

V charge in 1 M Na2SO4 (aq), and did not show any capacity fade upon extended cycling at both low and high rates.101

1.3.1.4 Birnessite δ-MnO2

Birnessite δ-MnO2 consists of 2D layers of edge-sharing MnO6 octahedra electrostatically stabilized by hexagonal interlayer arrays of water molecules and cations, which leads to a 7 Å interlayer spacing.14,90,104 It has been widely studied because it is easily synthesized and is similar to the layered oxides popular for Li-ion batteries. In addition, it is useful across a range of applications, from EES to Faradaic desalination to heavy-metal sorption, because it can

84,85,105–108 accommodate a variety of cations. Practically, the main drawback of the MnO2 polymorphs, including birnessite, is their low conductivity. When the MnO2 layers are doped with

0.5 – 1 % first row transition metals, additional sites are formed in the band gap, the charge transfer resistance decreases, and the material capacity is increased from 83 to 145 F/g.18,109 Doping the

110 MnO2 layers with point defects has similar results. Birnessite has also been studied in alkaline electrolytes as a catalyst for water splitting.111 Pinaud et al. show that in 0.1 M NaOH the 2.1 eV band gap of birnessite MnO2 lies within the potential stability window of water, which suggests that the band gap of birnessite also overlaps the stability window of neutral pH water.111

The relatively low surface energy of birnessite MnO2 provides little driving force for crystal growth after precipitation,93 and typical syntheses result in high surface area nanocrystalline

particles without long-range crystallinity. The lack of crystallinity complicates detecting structural changes resulting from electrochemistry, and the high surface area welcomes speculation over whether ion insertion occurs or if the charge storage behavior is dominated by non-faradaic or faradaic reactions. The potential range between ~ 0 – 1 V vs. SCE generates the most debate.

Within this range, birnessite typically has a capacity of ~ 42 mAh/g (150 F/g over 1 V), and possesses a primarily rectangular CV with broad redox peaks. Scientific literature generally accepts the possibility of two processes: 1) surface redox adsorption/desorption and 2) ion insertion/intercalation into crystalline material, site and ion size permitting.17,88,99,112 At potentials beyond the 0 – 1 V, a third charge storage mechanism is possible: dissolution and re-deposition of

Mn.23,113 This 2e- process leads to high capacity (1100-1400 F/g) but requires addition of Mn salts to the electrolyte to maintain a steady supply of the mobile Mn2+ close to the electrode surface.23

Over 0 – 1 V vs. SCE, the proposed charge storage mechanism has been described by surface redox and ion insertion, where A+ is a proton or a metal cation:

+ − 푀푛푂2 + 푥퐴 + 푥푒 ↔ 퐴푥푀푛푂2

Electrochemical quartz crystal microbalance studies show that this reaction is oversimplified, and multiple species are involved in the charge storage reactions.26,114 The apparent areal capacity based on gas adsorption surface area measurements indicates that faradaic processes must significantly contribute to the charge storage,85,115 but these surface area measurements can be erroneous,14,88 leading some to suggest that charge storage occurs due to increased surface

116 adsorption by the extension of the EDL into the material interlayer. Although MnO2 does not go through a semiconductor-to-metallic transformation and so lacks a large number of free charge carriers that would enable pure EDL behavior,117,118 in some structures free charge carriers may be available for polarization since the cathodic potential is within the conduction band.23,81,98,111,119

Arguments also vary on the proposed faradaic reaction mechanism. Some claim that Mn- based redox occurs due to the intercalation of alkali cations120,121 or H+ which then exchanges with an alkali cation from the electrolyte.122 Depending on the electrolyte, there may be coordinated, or uncoordinated movement of structural water molecules as well.77,114,123 Surface chemistry (via a negative zeta potential) indicates that cations will be the primarily attracted species during neutral- pH aqueous electrochemistry.108,124–126 Both energy dispersive X-Ray spectroscopy (EDS) and inductively-coupled plasma optical emission spectroscopy (ICP-OES) indicate that alkali cations contribute to at least some of the charge storage mechanism.15,127 However, while birnessite is considered attractive as a pseudocapacitive, high longevity, and high capacity aqueous cathode materials, its exact energy storage mechanisms are still unknown. Chapter 4 of this dissertation is devoted to uncovering these mechanisms.

1.3.1.5 Intergrowth γ-MnO2

The intergrowth phase consists of randomly intertwined regions of β-MnO2 with the 2x1 tunnels of the Ramsdellite phase. Also called electrolytic MnO2 (EMD), γ-MnO2 is the phase most

2 commonly formed by electrodeposition. Some reports describe EMD as ε-MnO2, which is

128,129 significantly less stable than, and can easily be transformed to, γ-MnO2. Prior to widespread secondary battery development, γ-MnO2 was used as the cathode material in alkaline and Zn-C dry cell primary batteries. In EES devices, reported capacitances vary from 23 – 107 F/g between 0-1

V vs. SCE depending on synthesis conditions.130 Here proton insertion is expected to dominate as the 1x1 and 1x2 tunnels of γ-MnO2 are not large enough to accommodate alkaline cation insertion, and the charge storage behavior is EDL-dominated at rates above ~ 10 mV/s.2,88,130

1.3.2 Manganese-Based Oxides

Other types of manganese-rich oxide materials include those of the form AxMO2, where A is an alkali cation such as Li+, Na+, or K+, and M is a transition metal or combination thereof— typically from the first row. Both the structure and the atmospheric stability of NaxMO2 are determined by structural cation content.131–134.134–137 Tunnel structures form at x < 0.44, and various layered structures form at 0.33 < x < 1.131–134 Cation content, which relates to the open circuit potential of the material, relates inversely to atmospheric stability. Batteries cannot store energy without a potential difference between the electrodes, so one electrode must be reduced upon assembly, meaning that it contains the inserting cation. Because cations are often intercalated at potentials below the reduction potential of water (3.94 V vs. Na/Na+), many materials synthesized in a fully reduced state spontaneously oxidize upon exposure to water and air.138 This substantially reduces the number of materials compatible with ambient processing and aqueous electrolytes. For example, a material with x = 1 will almost always form an impurity phase with a lower sodium content upon atmospheric exposure,139 while the tunnel structures are quite stable.

The tunnel structures exhibit higher atmospheric stability because their low cation content means the M exists at higher oxidation states to stabilize the structure. In the manganese-based layered structures, the Jahn-Teller distortion of manganese requires additional transition metal content in order to improve the cycling stability.19 The Jahn-Teller distortion occurs when Mn3+ is in a high spin state, and the MnO6 octahedron distort to reduce degeneracy, as in Figure 6. This adds more stress into the material and reduces the cyclability of manganese-based layered AxMO2. Additional transition metal content reduces the amount of Mn available to change between the 3+/4+ oxidation state. Materials of this type are common cathodes in non-aqueous Li-ion batteries, and have been widely studied for Na- and K-ion batteries, where they have been engineered to optimize their

capacity (up to ~120 mAh/g).140–142 This high capacity is attractive for aqueous EES, but the corrosive ability and low potential stability window of water complicate the development of compatible electrode materials.

Figure 6. Schematic of the Jahn-Teller distortion of Mn3+. Two distortions are shown that slightly alter the energy levels of electrons in the t2g orbital, stabilizing them rather than forcing them to maintain the same energy level. These elongations and compressions cause cyclic stress in the material, leading to structural degradation with extended cycling. Reproduced from Ref. 3 with permission. Copyright 2017 by the Royal Society of Chemistry.

1.3.2.1 Tunnel-Structured NaxMO2

Because of its reversibility, rate capability, and long-term structural stability, the tunnel- structured Na0.44MnO2 (Na4Mn9O18) has been widely studied as a cathode for aqueous electrolytes and Faradaic electrochemical desalination.8,70,141–146 These behaviors are surprising, given the many phase transformations that occur during electrochemical cycling.8,131,141,145,147 The

+ + orthorhombic crystal structure of Na0.44MnO2 has 2 x 2 and 1 x 3 tunnels containing Na , Li , or

K+, although only the sites in the 2 x 2 tunnels (Fig. 7A) are electrochemically active.146

Unfortunately, this means that less than half of the theoretical ~ 120 mAh g-1 capacity is

+ 134,142,146 available—further Na deintercalation releases O2 from the structure. Figure 7B and C show early studies by Whitacre et al. using this tunnel-structured oxide as an aqueous Na+ battery

144,145 -1 + cathode material. They obtained 45 mAh g at 0.125 C in 1 M Na2SO4 (0.22 Na per MnO2), most of which was still available after 1000 cycles.144 Later work focused on increasing capacity by substituting some Mn with other first row transition metals.134,142 This increases the Na+ content and increases the fraction of Mn3+, which can then oxidized instead of the lattice oxygens.142,148–

150 Using Ti and/or Fe allowed advances such as: maintaining the initial 45 mAh/g capacity at 16 times the rate,142 suppressing the phase transformations,134,142,146 and increasing the capacity to 76

-1 142 mAh g . This illustrates how vital transition metal composition is to performance of metal oxides.

Figure 7. Crystal structure and electrochemical performance of Na0.44MnO2. A) Crystal structure model showing the mobile Na+ in the Na(2) and Na(3) sites. Reproduced with permission from

-1 -1 (dQ dV ) from galvanostatic cycling at 25 mA g in a 1 M Na2SO4 aqueous electrolyte, where each peak denotes a phase transformation. Reproduced with permission from Ref. 131. Copyright

Figure in this configuration was initially published in Ref 1. Reproduced by permission of The

Royal Society of Chemistry.

1.3.2.2 Layered P2 NaxMO2

There are many variations on layered NaxMO2, but we will limit this discussion to the P2

+ type, a layered hexagonal structure consisting of alternating layers of Na and MO6 edge-sharing octahedra. The Na+ occupy trigonal prismatic sites (P), and the oxygen layers are arranged in an

…ABBA… stacking sequence along the c-axis (2) (Figure 8).151 When interlayer Na+ has been removed so that x < 0.35, NaxMnO2 and NaxNi0.22Co0.11Mn0.66O2 both rapidly form hydrated structures upon atmospheric exposure.140,152 The intercalated water molecules in the half-empty

+ Na sites counteract the electrostatic repulsion between MO2 layers, which typically leads to the layer glide experienced upon cycling in non-aqueous electrolytes.137,140

The research in Chapters 2 & 3 was born out of the fact that while many have studied the reactivity of P2 in air,137,140,152–155 few have studied their aqueous electrochemistry.9 One of the few trends is that if the transition metals form an ordered superstructure arrangement within the layers, or if the transition metal layer contains Cu, the oxide may be atmospherically stable. So far, this is true of 2/3 materials reported stable: Na0.67Ni0.33Mn0.67O2 and Na0.67Ni0.33-xCuxMn0.67O2, (0

< x < 0.33) both exhibit transition metal ordering, and while Na0.78Fe0.22Cu0.11Mn0.67O2 does not, it does contain Cu.110,112,129 Other compositions, including combinations of Mn, Ni, Fe, Zn, Co Ti, etc., form hydrated phases upon atmospheric or water exposure.136,137,152,154–156 In some, H+ from water exchanges with Na+ and can possibly dissolve the Mn from these acid-sensitive oxides.154,157,158

Although the P2 oxides are attractive for their high theoretical capacity, not all of it is accessible within the stability window of aqueous electrolytes. Some of the few studies of P2 materials in aqueous electrolytes have reported capacities of 41-62 mAh/g, but while these materials are electrochemically active, they also exhibit poor cyclability.9,62,137 Overall, their

17,159 performance is worse than that of δ-MnO2. However, their susceptibility to water uptake and composition-dependent response made them valuable to understand the effect of interlayer chemistry on aqueous EES, which we will discuss in the next section.

+ Figure 8. Structure of P2-NaxMnO2 where Na occupies two prismatic interlayer sites, MnO6 octahedra form edge-sharing layers, and the oxygen stacking sequence is “…ABBA…”.

In non-aqueous electrolytes, P2 oxides have a wide range of electrochemical behavior depending on the transition metal content, with capacities between 90 - 216 mAh g-1.160,161 For example, substituting Cu for some of the Mn content increases the material conductivity and lessens the extent of the Jahn-Teller distortion, also allowing the material to experience a solid- solution mechanism during charging rather than the multiple phase changes present in other composition.153,162–165

1.4 Tuning Material Behavior Post-Synthesis

As mentioned above, the electrochemical behavior of a given crystal structure can be greatly affected by changing their transition metal composition. Another common technique used to tune material behavior is by additional processing after the initial synthesis, such as exfoliation of bulk crystals into nanosheets, addition of vacancies, and incorporation of structural water. Each of these approaches improves the cyclability, rate capability, and capacity of EES electrodes.

Both electrochemical and chemical exfoliation are often used to make 2D sheets of

15,110,166–171 birnessite, graphite, and MoS2. The electrochemical techniques apply a current or voltage to a large crystal to force the intercalation of electrolyte species. The host material is subsequently exfoliated by gas bubbles formed upon the decomposition of these electrolyte molecules.166–168 The chemical techniques can be done on small, even nanoscale initial particles, and are therefore common in processing birnessite particles. They exfoliate the oxide into nanosheets by osmotic pressure, first removing the initial interlayer cations in acidic solution, and subsequently forcing the layers apart with the intercalation of bulky cations from a basic solution, a process that takes days to weeks with stirring,172,173 or hours with sonication.110 This process results in 2D nanosheets that can be restacked into porous electrodes with higher rate capability.15

Defects such as structural vacancies can also be used to improve the rate capability and capacity of transition metal oxides. For example, misplacing Mn atoms in birnessite into surface

Frenkel defects via acid treatment improved the capacity from 55 to 83 mAh/g at 0.2 A/g, and reduced the charge transfer resistance from 30 to 15 Ω.110 While otherwise outside the scope of this dissertation, high temperature heat treatments in a reducing atmosphere have been shown to

2- 174 improve capacity and rate capability in MoO3 by inducing O vacancies.

Finally, a common way of tuning the performance of a material is by altering the contents of the interlayer. For example, interlayer water has been shown to improve the rate capability and

175–180 cyclability of V2O5, WO3, and MnO2. It is hypothesized that interlayer water can electrostatically “shield” intercalating cations from the transition metal oxide layers, facilitating even the intercalation of multivalent cations.106,181,182 While the exact mechanisms are not yet known, materials with hydrated interlayers are promising for high rate aqueous EES.

1.5 Summary

Thus far, we have explored the foibles of aqueous electrolytes, discussed the two main mechanisms of EES, and described the behavior of a variety of manganese-based oxides. How then do all these topics fit together to make up a PhD? In short, the structure and composition of the electrode material determine how it interacts with the electrolyte, and what types of charge storage reactions occur. We have already discussed how the spinel λ-MnO2 can go from dissolution/solidification behavior to EDL behavior depending on electrolyte and potential window. Another example is the transition metal-dependent atmospheric stability of P2 oxides, which can be tuned by the contents of the transition metal oxide layers.

While aqueous electrolytes offer significant challenges, they also offer significant opportunities for EES as well as related applications in water treatment and element recovery. To implement them, we must understand and eventually be able to dictate how the electrolyte interacts with the electrode. In the next three chapters, we will look at three aspects of the interplay between aqueous electrolytes and layered manganese-rich transition metal oxides. Overall, the goal is to understand how the interlayer environment contributes to the energy storage mechanisms. To achieve this, I performed materials synthesis as well as physical and electrochemical characterization techniques, and worked closely with collaborators to do operando and in situ

characterization. Materials synthesis was selected based on the hypothesis of the research project and included electrochemical and solid-state methods. Physical characterization techniques such as X-ray diffraction, scanning electron microscopy, and Raman microscopy were used to connect the structure and morphology of materials to their processing conditions and electrochemical behavior. Electrochemical characterization techniques provided the fundamental driving force for the EES mechanisms to take place and were coupled to other methods for operando and in situ characterization. When put together, the variety of methods I use in my dissertation illuminate fundamental mechanisms of layered manganese-rich oxides undergoing EES in aqueous electrolytes. In Chapter 2, we study four compositions of P2 oxides to determine their structural and electrochemical response to aqueous electrochemistry. We determined that the material forms composition-dependent birnessite-like structures while retaining their initial bulk particle morphology. This work demonstrated that P2 oxides are not suitable for use as electrode materials in aqueous electrolytes. However, it then paved the way for Chapter 3, where we investigate the charge storage behavior of these bulk hydrated particles, and establish their viability as an activated carbon alternative. Finally, in Chapter 4 we conduct a multi-modal study of a model pseudocapacitive material, birnessite, to investigate whether the capacitive charge storage mechanism should be considered faradaic or non-faradaic. Chapter 5 offers a brief summary, as well as an outlook on the field as a result of this work.

CHAPTER 2

Charge Storage Mechanism and Degradation of P2-Type Sodium Transition Metal Oxides

in Aqueous Electrolytes

Preface

The work in this chapter was published as “Charge Storage Mechanism and Degradation of P2-Type Sodium Transition Metal Oxides in Aqueous Electrolytes” by Shelby Boyd, Rohan

Dhall, James M. LeBeau, & Veronica Augustyn, in the Journal of Materials Chemistry A, (J.

Mater. Chem. A, 2018,6, 22266-22276, DOI: C8TA08367C). Here the published main text and the supplementary information were intercalated to improve the chapter readability. Scientifically, this project was the first to fully investigate the structural and electrochemical behavior of P2 oxides upon aqueous electrochemistry, and the effect of interlayer chemistry on this behavior. As mentioned in the introduction, faradaic charge storage reactions require redox potentials of the material to lie within the electrolyte stability window. For this study, we chose a few compositions of P2 oxides that showed non-aqueous electrochemistry at potentials overlapping with the stability window of water and investigated how altering the transition metal chemistry tuned the material behavior in aqueous electrolytes.

2.1 Abstract

Few transition metal oxides exhibit sufficient stability for aqueous ion intercalation from neutral pH electrolytes for low-cost aqueous Na+ batteries and Faradaic desalination. P2 layered

Na+ manganese-rich oxides have high theoretical capacities and voltages for Na+ storage and are extensively investigated for non-aqueous Na+ batteries. However, the charge storage mechanism and factors controlling interlayer chemistry and redox behavior of these materials in aqueous electrolytes have not been determined. Here, we take a significant step in establishing their aqueous electrochemical behavior by investigating a series of P2 oxides that exhibit a range of stability in water and ambient air: Na0.62Ni0.22Mn0.66Fe0.10O2 (NaNMFe), Na0.61Ni0.22Mn0.66Co0.10O2

(NaNMCo), Na0.64Ni0.22Mn0.66Cu0.11O2 (NaNMCu), and Na0.64Mn0.62Cu0.31O2 (NaMCu).

Depending on the transition metal composition and potential, all materials exhibit significant irreversible Na+ loss during the first anodic cycle followed by water intercalation into the interlayer. The presence of water causes conversion into birnessite-like phases and microscopic exfoliation of the particles. The interlayer affinity for water is primarily driven by the Na+ content, which can be tuned by the transition metal composition and the maximum anodic potential during electrochemical cycling. The interlayer water affects the reversible capacity and cycling stability of the oxides, with the highest reversible capacity (~ 40 mAh g-1 delivered in ~ 30 minutes) obtained with NaNMCo. These results present the first studies on the structural effects of aqueous electrochemistry in P2 oxides, highlight the significant differences in the electrochemical behavior of P2 oxides in aqueous vs. non-aqueous electrolytes, and provide guidance on how to use the transition metal chemistry to tune their aqueous charge storage behavior.

2.2 Introduction

Electrochemical energy storage devices operating in neutral pH electrolytes are attractive because of their low cost and high safety. However, few transition metal oxides exhibit sufficient stability for electrochemical aqueous ion intercalation at neutral pH conditions, as indicated by their Pourbaix diagrams.1 Among these, layered manganese (Mn) oxides are of interest for aqueous sodium-ion (Na+) electrochemical energy storage11 and battery-type desalination83 due to their redox activity and the abundance and safety of manganese.183 The most widely-studied Mn-rich

+ oxides for Na intercalation from aqueous electrolytes are the layered birnessites, AxMnO2∙nH2O

(where A represents alkali cations such as Na+ and Mg2+), with capacities up to 134 mAh g-1.17 The complex interlayer of these oxides includes structural water and cations such as sodium, potassium, and magnesium, which makes them relevant for both mono- and multivalent aqueous energy storage devices.17,106

Higher capacities and voltages for Na+ intercalation have been obtained with P2 layered oxides (Na0.67Mn1-xMxO2, where M can be a variety of transition metals like Cu, Co, Fe, etc. and their combinations) in non-aqueous electrolytes, with reversible capacities of 90 - 216 mAh g-

1.160,161 The P2 terminology developed by Delmas, et al. indicates that the prismatic sites (“P”) between the metal oxide layers are occupied by Na+ and that the layers of edge-sharing transition metal oxide octahedra are arranged in an …ABBA… stacking sequence (“2”), as depicted in

Figure 1a.151 These materials are of potential interest as high voltage cathodes for aqueous Na+ batteries and desalinators because they are electrochemically active at anodic potentials within the limited 1.23 V thermodynamic stability window of aqueous electrolytes,57,160,161 and have high theoretical capacities, both of which could give rise to high energy density devices. While the intercalation behavior of these materials in non-aqueous electrolytes is fairly well

established,19,135–137,140,152,154,160,161,184–186 little is known about their behavior in aqueous electrolytes, where the presence of water is likely to lead to entirely different intercalation

+ phenomena. Recent studies on P2 Na0.67Ni0.33Mn0.67O2 and Na0.67Ni0.25Mn0.75O2 in aqueous Na electrolytes showed reversible capacities between 42 – 56 mAh g-1,9,187 but did not provide significant insights into the mechanism, effects of material chemistry on electrochemical behavior, or interlayer affinity for water. In the present work, we perform a systematic study of these fundamental characteristics of P2 oxides and identify the implications for their behavior in aqueous electrolytes.

Water is a unique non-flammable solvent with a higher solvation strength than the standard carbonate-based non-aqueous electrolyte solvents, which leads to higher-conductivity electrolytes.8,62,188 Due to their high polarity and small size, water molecules strongly solvate electrolyte cations such as Na+ and are expected to co-intercalate into materials upon

188,189 + electrochemical cycling. The possibility of hydronium (H3O ) intercalation also needs to be considered in aqueous electrolytes.190 The combination of water and oxygen or carbon dioxide oxidizes and hydrates many P2 layered oxides by spontaneously removing Na+ and replacing it with water.135–137,152,154–156,180,191 Previous work on P2 oxides cycled in non-aqueous electrolytes has shown that the reactivity to moisture varies with transition metal composition, where

Na0.67Mn0.66Ni0.33O2 is stable in water, but Na0.6MnO2, Na0.67Mn0.66Ni0.22Co0.11O2, and

Na0.67Mn0.5Fe0.5O2 exhibit spontaneous water and carbonate intercalation upon exposure to water or humid air.136,137,152 While the cause of enhanced stability has not been determined, one observed trend is that materials with a superstructure ordering of the transition metals within the oxide layers, such as Na0.67Mn0.66Ni0.33O2 and Na0.67Ni0.33-xMn0.66CuxO2, (0 ≤ x ≤ 0.33) exhibit significantly higher stability in water.135,137

Here, we take a significant step in establishing the effects of transition metal composition on the interlayer affinity for water and aqueous electrochemical behavior of P2 oxides. By synthesizing and characterizing four compositions that exhibit a range of stability in water and ambient air: Na0.62Ni0.22Mn0.66Fe0.10O2 (NaNMFe), Na0.61Ni0.22Mn0.66Co0.10O2 (NaNMCo),

135–137,140 Na0.64Ni0.22Mn0.66Cu0.11O2 (NaNMCu), and Na0.64Mn0.62Cu0.31O2 (NaMCu) we demonstrate that the transition metal composition affects the affinity of the interlayer for water intercalation and in turn, the electrochemical charge storage behavior. Using structural and electrochemical characterization techniques, we show that these P2 oxides transform to a hydrated birnessite-like phase upon aqueous electrochemical cycling and that the transformation is driven by the redox potential at which a critical amount of Na+ remains (~ 0.4 Na+ per formula unit) in the interlayer. The phase transformation to a hydrated layered structure is accompanied by significant exfoliation of the layered structures. These results demonstrate that the transition metal composition of layered oxides has a significant effect on the interlayer affinity for water, which in turn affects the structural stability and electrochemical activity in aqueous electrolytes.

2.3 Methods

2.3.1 Material Synthesis

The P2 oxides were synthesized by room temperature coprecipitation of transition metal hydroxides and subsequent high-temperature calcination into sodiated transition metal oxides.

Specifically, precursor solutions of 0.53 M transition metal acetates [Mn(CH3COO)2∙4H2O,

Co(CH3COO)2∙4H2O, Ni(CH3COO)2∙4H2O, Fe(CH3COO)2, and Cu(CH3COO)2, Alfa Aesar] in deionized (DI) water were prepared according to the following molar ratios: (a) 11 : 66 : 22, Co :

Mn : Ni, (b) 11 : 66 : 22, Fe : Mn : Ni, (c) 11 : 66 : 22, Cu : Mn : Ni, and (d) 34 : 66, Cu : Mn.

Each solution was added to 2.25 M aqueous NaOH (Fisher Scientific) solution at ~ 2.5 mL min-1.

After precipitation, the hydroxides were washed to pH ~ 7, filtered, dried at 120°C, and ball milled in ethanol with 5 mm spherical zirconia beads (U.S. Stoneware) for 24 hours. The dried ball-milled hydroxides were mixed into an aqueous NaOH solution with 0.704 mol Na+ per mol of transition metal hydroxide to target a final composition of 0.64 Na+. This solution was stirred for 1 hour at room temperature and then at 100°C until dry. The dry powder was annealed in a box furnace

(Thermo Scientific) in air at 500°C for 5 hours, cooled to room temperature and ground with a mortar and pestle for 15 minutes before fully calcining at 850°C for 6 hours. All samples were transferred from the furnace while above 100°C to an argon-filled glovebox (MBraun Labstar Pro) with < 0.5 ppm O2 and H2O to protect them from the ambient atmosphere, and ground with mortar and pestle for 30 minutes.

2.3.2 Physical Characterization

The composition of each oxide was analyzed with an inductively-coupled plasma optical emission spectrometer (ICP-OES; Perkin Elmer 8000). 50 mg of each sample was dissolved in aqua regia at 70°C for two hours. All reagents, standards, and samples only contacted polypropylene to avoid accidental leaching of Na from glass. X-ray diffraction (XRD) was performed on an X-ray diffractometer in standard Bragg-Brentano geometry with Cu-Kα radiation

(PANalytical Empyrean). Powder samples were rotated at 7.5 RPM, while electrode samples for ex situ XRD were stationary. Lattice parameters were determined by Rietveld refinement using the GSAS-II software. The morphology of the electrodes and pristine powders was characterized using a field emission scanning electron microscope (FEI Verios 460L). Reactivity of the as- synthesized powders upon water exposure was tested by stirring the ground powders in DI water

(20 mg mL-1) for 8 days. The excess water was then centrifuged off, and the damp powders were used for XRD, scanning transmission electron microscopy (STEM), and thermogravimetric analysis (TGA).

Samples for STEM were prepared by sonicating the ground pristine powder in ethanol (1 mg mL-1) for 30 minutes, diluting to 150 μg mL-1, and dropcasting 15 μL onto lacey carbon TEM grids (Pelco) before drying at 100°C in air. Samples of the water-exposed powders were prepared by sonicating in water for 30 minutes, diluting to 200 μg mL-1, and dropcasting 20 μL onto the lacey carbon TEM grids. These grids were dried overnight at room temperature. The samples were imaged using a probe corrected scanning transmission electron microscope (FEI Titan G2), equipped with a high-brightness field emission gun (X-FEG) and operated at 200 kV. For structural characterization, high-angle annular dark-field (HAADF) images were acquired with a collection inner semi-angle of 77 mrad. The interlayer distances were then directly measured and averaged from several particles. Energy dispersive X-ray spectroscopy (EDS) was used to determine the elemental composition of the synthesized compounds using a FEI Super-X EDS detector with a large solid angle (~ 0.7 sr).

TGA was conducted on a SII EXSTAR6000 TG/DTA6200. Dry samples were tested immediately after removal from the glovebox. Water-exposed samples (for 16 days) were first dried for ~ 20 minutes at 50°C, until they formed a slightly damp powder. All samples were tested in aluminum pans between 25 - 300°C using a ramp rate of 5°C min-1 in air.

2.3.3 Electrochemical Characterization

Electrochemistry was conducted in a glass three-electrode 50 mL round bottom flask using a 1 M Na2SO4 (Sigma Aldrich) electrolyte, a platinum wire counter electrode (99.997%, Alfa

Aesar) and a Ag/AgCl in saturated KCl reference electrode (Pine Instruments). Slurries of active materials were made with 80 wt.% active material, 10 wt.% acetylene black (Alfa Aesar), and 10 wt.% polyvinylidene fluoride (PVDF; Arkema Kynar KV 900) ground together for 5 minutes and stirred overnight in n-methyl pyrrolidone (NMP; Sigma Aldrich) at 990 RPM. An acetylene black slurry was prepared in a similar fashion but without the oxide, containing 67 wt.% acetylene black and 33 wt.% PVDF. Electrodes were made by pasting the slurries onto a ~ 1 cm2 area of a 1 x 2 cm titanium mesh (Alfa Aesar) with active material mass loadings of 1 - 3 mg cm-2, and drying at room temperature for at least 6 hours before drying at 120°C overnight. Ni-plated stainless steel alligator clips were used to hold the working and counter electrodes in the electrolyte. When setting up these aqueous cells, care must be taken to not get the alligator clips wet, or they will rust, increasing the resistance and contaminating the cell. To determine the electrochemical response of all four oxide compositions, cyclic voltammograms (CVs; Bio-Logic MPG-2) were collected at

0.1 mV s-1 between 0 - 0.8 V vs. Ag/AgCl (2.9 - 3.71 V vs. Na/Na+). Unless otherwise noted, all potentials referenced in this work are vs. Ag/AgCl. Cycling stability of NaNMCo and NaMCu was characterized at 0.5 mV s-1 for 50 cycles between both 0 – 0.8 V and 0 – 1.1 V. Electrochemical impedance spectroscopy (EIS; Bio-Logic VMP-3) was conducted from 100 mHz to 200 kHz with a 10 mV amplitude at the open circuit potential on the pristine electrodes and after 10 cycles at 0.5 mV s-1. To determine whether the redox potential was affected by a change in electrolyte pH

+ + -1 (which would indicate H /H3O intercalation), cyclic voltammetry was performed at 1 mV s in

Na2SO4 electrolytes, with the addition of varying amounts of NaOH to increase the pH, which was measured using a pH meter (Mettler Toledo FiveEasy). In electrolytes of pH 6, 9, 11, and 13, electrodes were cycled between 0 - 0.6 V due to the high OER activity in the pH 13 electrolyte.

Additionally, electrodes were cycled between 0 – 0.8 V in electrolytes of pH 6, 9 and 11.

2.4 Results and Discussion

2.4.1 General Results

The aqueous electrochemical behavior of P2 Mn-rich oxides, including the effects of transition metal composition on the electrochemical behavior and interlayer water affinity, was investigated in four oxides (“NaNMFe,” “NaNMCo,” “NaNMCu,” and “NaMCu”) with varying degrees of moisture sensitivity. Table I shows the compositions determined by ICP-OES, which verify that the final Na content and M ratios were close to the intended composition. Rietveld refinement of the XRD patterns in Figure 1 confirmed that all four compositions formed the expected P2 phase with the hexagonal space group P63/mmc. Figure 2 shows the refinement results at higher diffraction angles. NaNMFe, NaNMCo, and NaNMCu were refined as a single phase, while NaMCu was refined as 89.7 wt% P2 with 10.3 wt% CuO. Results from the refinement, also in Table 1, show little variation in lattice parameters with changes in transition metal composition. There is ~ 1% change in the a-lattice parameter between NaNMCo and the other compositions, but this value is in agreement with the reported refinement results.157 The ICP-

OES results and the similar c lattice parameters indicate that all compositions contain about the same amount of Na+ in the as-synthesized condition. The XRD results also show that the NaNMCu and NaMCu exhibited two superlattice ordering peaks at 27.25 and 28.47 °,135,192 which were not included in the Rietveld refinement. The larger ionic radii of Ni2+ and Cu2+, as compared to Mn3+ and Mn4+, promote formation of a √3a × √3a hexagonal superlattice, especially in compositions with a 2 : 1 ratio of Mn : Cu, Ni, or Ni and Cu,135,192,193 which leads to Na+/vacancy ordering.185

The similar radii of Co3+, Fe3+, Mn3+, and Mn4+ allow random cation mixing and disrupt this ordering.192,193

Table I. Composition (from ICP-OES) and lattice parameters (from Rietveld refinement) of the P2-type Na0.6Mn0.66M0.34O2. Material Composition a (Å) c (Å) Rwp GOF

NaNMFe Na0.62Ni0.21Mn0.62Fe0.10O2 2.893487 11.188151 4.681 3.47

NaNMCo Na0.61Ni0.21Mn0.62Co0.10O2 2.864602 11.200887 5.572 4.18

NaNMCu Na0.64Ni0.22Mn0.66Cu0.12O2 2.891256 11.15571 4.663 2.84

NaMCu Na0.64Mn0.62Cu0.31O2 2.89903 11.17451 4.68 2.65 Rwp: weighted profile R-factor; GOF: goodness of fit

Figure 1. Structure of as-synthesized materials: a) schematic illustrating the P2 structure with alternating MO2 (where M is 0.64 Mn and 0.34 Cu or 0.22 Ni and 0.11 Fe, Co, or Cu) layers of edge-sharing octahedra and interlayer Na+. The refined XRD patterns show that each of the four compositions crystallizes into this structure: b) NaNMFe, c) NaNMCo, d) NaNMCu, and e)

NaMCu. The colored tick marks show the location of the P2 peaks in each graph. The gray tick marks in e) show the CuO peaks.

Figure 2. High angle XRD fitting of the Rietveld refinements for: a) NaNMFe, b) NaNMCo, c)

NaNMCu, and d) NaMCu and CuO. The tick marks at the bottom of each graph represent the P2 peak locations in each material, while the gray (bottom) tick marks in d) represent CuO.

As shown by the SEM images of pristine electrodes in Figure 3, all four materials have similar sub-micron primary particles, with larger, micron-size secondary particle aggregates throughout. The faceted crystals of the active materials show the hexagonal basis of this crystal structure.

Figure 3. Scanning electron micrographs of electrodes of each composition of the P2 oxides: a)

NaNMFe, b) NaNMCo, c) NaNMCu, and d) NaMCu. The particle size and morphology does not vary with the transition metal composition.

To further characterize the structure and composition, HAADF-STEM imaging and corresponding EDS elemental mapping were performed on a particle of NaNMCo. Figure 4a shows that in agreement with the XRD results, the material crystallizes in a layered structure. The interlayer spacing, as measured from the HAADF-STEM image, is ~ 5.8 Å. The composition maps for each individual element in NaNMCo (Figure 4b-f), and a composite EDS map of Na and Mn

(Figure 4g) demonstrate that as expected, the transition metals reside within the metal oxide layers, while the Na+ resides in the interlayer.

Figure 4. Structure and composition of an individual particle of NaNMCo: a) HAADF-STEM image showing the layered structure with an average interlayer spacing of 5.8 Å; corresponding

EDS elemental mapping of b) Na, c) Ni, d) Mn, e) Co, and f) O; g) composite EDS elemental mapping of Na and Mn, which shows that Na is located between layers of Mn. HAADF-STEM images courtesy of Dr. Rohan Dhall.

2.4.2 Role of Transition Metal Composition on the Interlayer Affinity for Water

Water stability tests and aqueous electrochemistry were conducted to determine the mechanism of aqueous charge intercalation into P2 oxides as a function of transition metal composition. First, XRD and HAADF-STEM were used to understand the local structure of each composition before and after exposure to DI water for 8 days. The XRD data (Figure 5) shows that after water exposure, both the NaNMFe and NaNMCo exhibit a partial transformation to a phase with a larger interlayer spacing of ~ 7 Å as indicated by the emergence of a new peak at ~

12.5 °. This is accompanied by a loss of Na+, shown by the decrease in the position of the P2 (002) peak at ~16 °.157,184,185 No phase transformation was detected in NaNMCu or NaMCu. The presence of a new phase with a larger interlayer spacing of ~ 7 Å in NaNMFe and NaNMCo implies the transformation into a hydrated, birnessite-like structure, which has been reported for

137 P2 materials without superstructure ordering. P2 NaxMnO2 and NaxNi0.22Co0.11Mn0.66O2

desodiated to x < 0.35 Na+ in non-aqueous electrolytes spontaneously intercalate water into the half-empty Na+ sites and form a phase with larger interlayer spacing when exposed to air.137,140,152

A similar mechanism is likely to occur in the water-exposed NaNMCo and NaNMFe.

Figure 5. Ex situ XRD of the four compositions of P2 oxides after water exposure for 8 days, showing that the NaNMFe and NaNMCo form a birnessite-like phase (♦) in addition to the P2 phase (*). Both NaNMCu and NaMCu retain the P2 phase, indicating improved stability in the presence of water as compared to NaNMFe and NaNMCo.

While XRD measures the average structural change, STEM provides a local measure of the effect of water exposure on the material structure, particularly the interlayer uniformity, lending insight into how transition metal composition affects interlayer chemistry in layered Na+ transition metal oxides. Figure 6 shows the STEM images of the layered structure for all four compositions before and after water exposure. The interlayer spacings measured with XRD and

STEM on powders, and XRD on electrodes after aqueous electrochemistry, are listed in Table II.

Raw data from the STEM measurements is listed in Table III. The pristine NaNMFe in Figure 6a

exhibits an irregular interlayer spacing, while the pristine NaNMCo, NaNMCu, and NaMCu

(Figure 6c, e, and g) all appear uniform with an average interlayer spacing ~ 5.8 - 5.9 Å. This uniformity is expected, as care was taken to protect the “pristine” samples from air exposure after synthesis. The irregular layers in Figure 6a show that the NaNMFe is the most reactive composition, and had already begun reacting with the atmosphere to form a partially hydrated structure. Figure 6b, d, f, and h show the water-exposed NaNMFe, NaNMCo, NaNMCu, and

NaMCu, respectively. The NaNMFe after water exposure has an increased average interlayer spacing of 6.16 Å, closer to the hydrated spacing of birnessite. The washed NaNMFe in Figure 6b appears more uniform than the pristine material, which could be due to more complete water intercalation into the interlayer, or because the area imaged on the water-exposed sample was thicker than on the pristine samples. After water exposure, NaNMCo (Figure 6d) exhibits turbostratic layering, which is indicated by the large standard deviation in the interlayer spacing measurement although the average value remains close to the pristine NaNMCo. After water exposure, the NaNMCu and NaMCu appear uniform and do not exhibit a significant change in the interlayer spacing as compared to the pristine material.

Table II. Interlayer spacing of the four compositions of P2 oxides measured with XRD and STEM for pristine, water-exposed, and electrochemically cycled samples. Material Pristine interlayer Interlayer spacing after Interlayer spacing after spacing (Å) water exposure (Å) electrochemical cycling (Å)

XRD STEM XRD STEM XRD NaNMFe 5.60 5.39 ± 1.00 5.62; 7.02 6.16 ± 0.59 5.67; 7.08 NaNMCo 5.62 5.78 ± 0.23 5.60; 7.00 5.67 ± 1.62 5.69; 7.08 NaNMCu 5.58 5.77 ± 0.14 5.56 5.29 ± 0.35 5.66; 7.02 NaMCu 5.58 5.90 ± 0.14 5.58 5.57 ± 0. 52 5.58

Table III. Raw data for the interlayer spacing calculations from STEM images. NaNMFe NaNMCo NaNMCu NaMCu Pristine Water- Pristine Water- Pristine Water- Pristine Water- (Å) exposed (Å) exposed (Å) exposed (Å) exposed (Å) (Å) (Å) (Å) 5.265 5.818 6.038 6.036 5.793 5.419 5.717 5.642 5.617 5.75 5.849 5.676 5.855 5.306 5.826 5.664 5.821 6.626 5.996 7.1* 5.824 4.681 5.652 6.48* 5.861 5.412 5.978 6.087 5.93 4.956 5.823 5.719 5.759 5.97 5.889 6.58 5.797 4.788 6.076 5.866 5.563 6.367 5.623 6.19 5.93 5.753 5.9 5.625 6.071 6.211 5.647 5.322 5.625 5.599 6.015 5.63* 5.991 5.62 5.651 5.754 5.626 5.45 6.018 4.42* ꝉ 2.644 7.488 5.319 7.04* 5.562 5.3125 5.958 5.34 6.34 4.52* 5.564 5.283 5.966 5.266 5.63 6.78* 5.629 6.72 5.02* 6.195 ꝉ Data point taken on 5 interlayer spacings.

*Data point taken on a single interlayer spacing

Unless otherwise noted, measurements were taken across 10 interlayer spacings (between

11 oxide layers) from HAADF-STEM images, using ImageJ.

Figure 6. STEM images of the layered structure of the four compositions of P2 oxides before (a, c, e, g) and after (b, d, f, h) water exposure (scale bar = 2 nm) indicate that the NaNMFe and

NaNMCo experience an increase in interlayer spacing with water exposure along with more interlayer spacing disorder, while NaNMCu and NaMCu retain the same interlayer spacing.

HAADF-STEM images courtesy of Dr. Rohan Dhall.

TGA was performed on each composition before and after water exposure to further characterize the effect of water intercalation into the interlayer (Fig. 7). The pristine materials exhibit a small amount of mass loss from water adsorption following their short (~30 minute)

exposure to ambient air. After water exposure, all four compositions exhibit increased mass loss between ~ 70 and 300°C that is due to the loss of both surface and interlayer water. The amount of water lost from NaNMFe and NaNMCo is significantly greater than that lost from NaNMCu and NaMCu, which correlates well with the variation in interlayer spacing before and after water exposure measured with XRD and STEM. Given the lack of interlayer spacing change in NaMCu from XRD and STEM, the mass loss from water-exposed NaMCu (~ 0.13 mol of H2O) is likely entirely due to adsorbed surface water. Also, given that the surface area, morphology, and hydrophilicity of each of the four compositions is similar, it can be assumed that all four materials exhibit similar amounts of surface-adsorbed water. With these assumptions and the TGA results, the compositions after water exposure are: NaNMFe·0.32H2O, NaNMCo·0.44H2O, NaNMCu, and

NaMCu, where the amount of water indicates structural water in the interlayer. Overall, both local and average structural characterization techniques demonstrate that the reactivity of layered oxides with water decreases when copper is substituted into the transition metal layer, consistent with prior studies.135,150,153,165

Figure 7. TGA of the pristine powders immediately after removal from the glovebox and of the water-exposed powders after 16 days. The pristine powders (dashed lines) show a small mass loss due to adsorbed water. Both a) NaNMFe and b) NaNMCo show clear steps corresponding to the removal of interlayer water, while c) NaNMCu and d) NaMCu show small steps that can be attributed to water adsorbed onto the surface.

The XRD, ICP-OES, SEM, and STEM results indicate that the as-synthesized materials of each composition are iso-structural, have similar Na+ content, and exhibit similar morphologies.

This permits the exploration of the effect of transition metal composition on the materials’

electrochemical activity in a neutral-pH aqueous Na+ electrolyte. Each composition was electrochemically cycled in a 1 M Na2SO4 electrolyte, which has a pH of ~ 6. Figure 8 shows the first and second CVs of each composition between 0 – 0.8 V at 0.1 mV s-1. All four P2 oxides exhibit electrochemical activity in this potential range, but in contrast to their similar structures and morphologies, each composition exhibits a unique electrochemical response. The first anodic cycle of all four compositions shows redox peaks, with a subsequent decrease in capacity and peak definition depending on composition. NaNMFe exhibits poorly-defined redox peaks and a semi- rectangular CV even in the first cycle, with no distinct peaks in the second cycle. NaNMCo exhibits defined redox peaks in the first cycle, but adopts a more rectangular, capacitive CV after the first cycle. NaNMCu exhibits more defined redox peaks than NaNMCo, and retains these peaks and a slightly higher capacity in the second cycle. NaMCu exhibits well-defined redox peaks in both the first and second cycle. This is a significant difference from the non-aqueous CVs of these P2 oxides, which typically exhibit defined redox peaks and little capacitive background.135,157,160,161

The development of more capacitive CVs is indicative of the lack of well-defined potentials for ion intercalation into the interlayer, which is similar to the electrochemical behavior of hydrated birnessite.180,190,194 Table IV shows the capacities and Coulombic efficiencies (CE) for the first and second cycles of all four materials. The most water-sensitive compositions, NaNMFe and

NaNMCo, show the highest 1st cycle capacities and highest CEs, indicating irreversible Na+ deintercalation during the first anodic sweep. The more water-stable materials exhibit more reversible electrochemistry with lower 1st cycle capacities and CEs nearer to 1.

Figure 8. Electrochemistry of the four compositions of P2 oxides in an aqueous Na+ electrolyte at

0.1 mV s-1: a) NaNMFe exhibits a semi-rectangular CV even in the first cycle, b) NaNMCo exhibits defined redox peaks in the first cycle and an almost rectangular CV in the second, c)

NaNMCu retains most of its redox peaks during the second cycle, indicating higher retention of the P2 phase, and d) NaMCu also retains most of its redox peaks and thus the P2 structure. “A.B” represents an acetylene black electrode on Ti mesh; it demonstrates that the measured current is primarily from the redox activity of the transition metal oxide particles in the electrode.

Table IV. Anodic capacities and Coulombic efficiencies of the four compositions of P2 oxides in 1 -1 M aqueous Na2SO4 electrolyte cycled at 0.1 mV s . Na+ 1st cycle anodic 2nd cycle anodic 2nd 1st cycle Initial Na+ remaining Material capacity capacity cycle CE content after 1st (mAh g-1) (mAh g-1) CE anodic cycle NaNMFe 47.7 2.30 16.6 0.90 0.62 0.39 NaNMCo 60.9 1.54 31.9 0.95 0.61 0.44 NaNMCu 32.0 1.58 19.5 1.11 0.64 0.52 NaMCu 30.4 0.99 24.9 0.97 0.64 0.52

The water exposure results and the varied electrochemical behavior of these four

compositions indicate that their structural response to electrochemical cycling in aqueous

electrolytes is not uniform. To investigate the intercalation mechanism in aqueous electrolytes in

this class of materials, ex situ XRD of the electrodes was performed before and after cycling at 0.1

-1 mV s in 1 M Na2SO4 electrolyte to determine the structural implications of aqueous

electrochemistry (Figure 9). Both NaNMFe and NaNMCo transform almost entirely to a phase

with a larger interlayer spacing of ~ 7 Å. While the formation of such a birnessite-like phase was

observed upon exposure to water (Figure 5), it is clear that electrochemical cycling leads to even

more water intercalation into the structure. NaNMCu partially transforms, and exhibits a two-

phase structure after cycling with some retained P2 phase, while NaMCu remains completely in

the P2 structure. These results indicate that electrochemical cycling leads to further water

intercalation into P2 oxides, but that this reactivity can be decreased by the substitution of copper

into the transition metal oxide layer.

Figure 9. Ex situ XRD of slurry electrodes before (a) and after (b) electrochemical cycling in 1 M

Na2SO4 aqueous electrolyte. a) Before electrochemical cycling, the (002) peak of the P2 phase is at the same position for all compositions indicating similar Na+ content and interlayer spacing. b)

After electrochemical cycling, NaNMFe and NaNMCu almost completely transform to a birnessite-like phase. NaNMCu partially transforms, while NaMCu retains the P2 phase and the highest final Na+ content, as indicated by the slightly higher position of the (002) peak at ~ 17 °.184

According to the initial composition of each material in Table I, and assuming no parasitic

+ + + reactions or H or H3O co-intercalation, the Na content after the first anodic cycle is 0.44 for

NaNMFe, 0.39 for NaNMCo, 0.52 for NaNMCu, and 0.52 for NaMCu. NaNMCo is the only material to be electrochemically oxidized to a Na+ content close to 0.35 Na+. However, Na+ is spontaneously extracted from these materials upon atmospheric or water exposure,136 so the actual final Na+ content is likely lower than predicted by the first anodic capacity. When cycled in non- aqueous electrolytes, the average redox potential of P2 oxides increases with substitution of a first row transition metal of increasing atomic number, from Fe to Cu.157,165,195 This higher redox potential means less Na+ can be extracted between 0 – 0.8 V, which causes the decreased water

intercalation during electrochemical cycling and the lower capacity of the Cu-substituted materials. The increased Na+ content stabilizes the material interlayer and reduces its affinity for water. According to this hypothesis, the NaMCu does not transform to a birnessite-like phase because its higher redox potential limits Na+ extraction in the aqueous electrolyte.

2.4.3 High pH Electrochemistry

+ + In an aqueous electrolyte, there is the possibility of H or H3O intercalation rather than

Na+ intercalation. To determine whether the intercalating species is Na+ or H+, pristine NaNMCo

-1 electrodes were cycled at 1 mV s in aqueous Na2SO4 electrolytes of pH 6, 9, 11, and 13 followed by XRD characterization. According to the Nernst equation,21 the potential at which intercalation or deintercalation occurs should shift with concentration of the intercalating species:

푅푇 [퐴+]푎 퐸 = 퐸0 + ln⁡ ( 표푥) 푛퐹 푎푟푒푑

where:

E°: formal potential

+ + + [A ]: concentration of Na or H

aox = ared: activity of the solid phases undergoing redox reaction

R: gas constant

T: temperature

- n: e transferred (~ 0.3)

F: Faraday constant

Here, the oxidized (ox) phase is Na0.6-xMO2, and the reduced (red) phase is Na0.6MO2. The activity of both of these solid phases is 1. Table V shows the calculated redox peak shifts from the 53

formal potential for electrolytes of pH 6, 9, 11, and 13, with n = 0.3 and T = 25°C. A redox peak shift of ~ 1 V (due to an electrolyte pH change from 6 to 13) would indicate H+ intercalation, while invariant redox peaks with increasing pH would indicate Na+ intercalation.21,58

Table V. Calculated redox peak shifts (from E°) for Na+ or H+ intercalation as a function of increasing electrolyte pH. pH Na+ (V) H+ (V)

6 0.059 -1.2

9 0.059 -1.8

11 0.059 -2.2

13 0.064 -2.6

If H+ were the intercalating species, the redox peaks would shift negatively and out of the investigated potential range (0 – 0.8 V) with increasing pH. For Na+ as the intercalating species, the redox peak shift would only increase by a maximum of 5 mV.

Figure 10a shows the CVs of electrodes cycled from 0 - 0.6 V in electrolytes of pH 6 to

13. During the first cycles, the redox peak potentials of the NaNMCo at each pH show little variation as H+ concentration decreases significantly from 10-6 M to 10-13 M. The as-prepared electrolyte had a pH of ~ 6, with 2 M Na+ to 10-6 M H+ and thus a significantly higher probability of Na+ intercalation than H+. The invariant redox peaks and similar current density as electrolyte pH varies strongly indicate that the intercalation mechanism is likely primarily due to Na+

+ 21,58,190 intercalation rather than H3O . Ex situ XRD (Figure 10b) was conducted to determine the

structural effects of electrochemical cycling with varying pH. The results indicate that regardless of pH, NaNMCo transforms into two phases after cycling to 0.6 V. Figure 11 shows the effect of cycling the NaNMCo to a higher anodic potential of 0.8 V as a function of electrolyte pH. The ex situ XRD (Figure 11b) results show that regardless of pH, when cycled to a higher anodic potential, NaNMCo almost completely transforms into the birnessite-like phase. This supports the hypothesis that the transformation to a hydrated birnessite-like phase is driven by the increased electrostatic repulsion between the oxygen anions across the interlayer as the amount of Na+ decreases during electrochemical cycling, which is determined by the maximum anodic potential.

Figure 10. Effect of the 1 M Na2SO4 electrolyte pH on the electrochemical behavior of NaNMCo: a) First cycle CVs of NaNMCo between 0 – 0.6 V show similar redox peak positions as a function of electrolyte pH, with slightly higher current response at pH 13 due to increased OER activity. b)

Ex situ XRD of the electrodes cycled to 0.6 V show the formation of two phases after cycling regardless of pH. Due to the limited Na+ extraction at 0.6 V, the electrodes cycled at each pH only partially transform to the birnessite-like phase.

Figure 11. a) First cycle CVs of NaNMCo between 0 – 0.8 V at pH 6, 9, and 11, showing similar redox peak positions as a function of pH. b) Ex situ XRD of the electrodes cycled to 0.8 V shows that by cycling to a higher anodic potential, NaNMCo (regardless of electrolyte pH) almost completely transforms into a hydrated birnessite-like phase.

2.4.4 Effect of Potential Window on the Interlayer Affinity for Water of P2 Oxides in

Aqueous Electrolytes

To test the hypothesis that the Na+ content remaining in the interlayer determines the interlayer affinity for water in P2 oxides cycled in aqueous electrolytes, NaNMCo and NaMCu were cycled between 0 – 0.8 V and 0 – 1.1 V (2.9 – 3.7 and 4.0 V vs. Na/Na+). These compositions were chosen because NaNMCo shows a phase transformation with water exposure and NaMCu showed no reactivity over the more narrow 0 – 0.8 V potential window. Figure 12 shows the CVs of both compositions over each potential window at 0.5 mV s-1. The additional 0.3 V does not alter the CV of NaNMCo (Figure 12a and b). However, the CVs of NaMCu cycled to 1.1 V (Figure

12d) shows the first cycle loss of redox peaks.

-1 Figure 12. Electrochemical cycling at 0.5 mV s in 1 M Na2O4 of a) NaNMCo from 0 – 0.8 V, b)

NaNMCo from 0 – 1.1 V, c) NaMCu from 0 – 0.8 V, and d) NaMCu from 0 – 1.1 V. Each has an acetylene black (“A.B.”) background at 0.5 mV s-1 for reference.

Figure 13a shows that the increase in anodic potential increases the first cycle anodic capacity from 65 to 83 mAh g-1 for NaNMCo, and from 29 to 60 mAh g-1 for NaMCu. The 0.5 mV s-1 sweep rate used for the cycling stability tests correlates to a 2.27C rate in a galvanostatic cycling experiment. At a ~ 2C rate in non-aqueous electrolytes over a ~ 1.5 – 2 V wide potential window, the capacities of these P2 oxides are 88 mAh g-1 for NaNMCo196 and ~ 45 mAh g-1 for

NaMCu.165 These values indicate that in the first anodic cycle, the electrochemical behavior of the

P2 oxides in aqueous electrolytes is similar to the non-aqueous electrolytes and that there is good utilization of the active material. Figure 13b shows that both NaNMCo and NaMCu cycled to 1.1

V experienced large irreversible anodic capacity loss in the first cycle. After 50 cycles at 0.5 mV/s, the XRD patterns (Figure 13c) show formation of a birnessite phase in both NaNMCo and NaMCu cycled to 1.1 V. This supports the hypothesis that the interlayer affinity for water is due to the amount of Na+ remaining in the interlayer as determined by the redox potential of the transition metals in the oxide, which is conceptualized in Figure 14. The broad XRD peak in the NaNMCo electrodes at ~ 18 ° was attributed to a contracted interlayer spacing observed at low Na+ content when cycling in non-aqueous electrolytes,165,197–200 and the new peak at ~ 24.5 ° may also result from the increasingly disordered structure.

-1 Figure 13. Cycling stability of NaNMCo and NaMCu at 0.5 mV s in 1 M Na2SO4 over two different potential windows. a) Anodic capacity, b) Coulombic efficiency, and c) ex situ XRD of the electrodes after 50 cycles at 0.5 mV s-1. * indicates the P2 phase, while ♦ indicates the birnessite phase.

Figure 14. Schematic of the transformation from a P2 oxide to a birnessite-type oxide with Na+ deintercalation in aqueous electrolytes. The electrostatic repulsion between facing oxygen anions increases the interlayer spacing of the P2 oxide with Na+ deintercalation. At a certain amount of

Na+ in the interlayer (~ 0.4 Na+ per formula unit), which can be controlled by the transition metal

M content and the applied maximum anodic potential Vmax, water is intercalated into the interlayer, transforming the structure to a birnessite-like phase.

The structural transformation into a birnessite phase also led to significant particle damage.

SEM images of NaNMCo and NaMCu before and after cycling to 0.8 and 1.1 V in Figure 15 show that the intercalation of water severely exfoliates and damages the oxides. This same damage occurred in NaNMCo after water exposure (and no electrochemical cycling) (Figure 16). The

NaMCu cycled to 0.8 V, which did not show a birnessite phase transition, did not have this same degree of damage.

Figure 15. SEM images showing the microstructural effects of water intercalation in P2 oxides. a) Pristine NaNMCo, b) NaNMCo after 50 cycles to 0.8 V, c) NaNMCo after 50 cycles to 1.1 V, d) pristine NaMCu, e) NaMCu after 50 cycles to 0.8 V, and f) NaMCu after 50 cycles to 1.1 V.

The water intercalation and transformation to a birnessite phase cause large sections of the particles to delaminate, and even fracture. All materials exhibited an increase in surface roughness with cycling, but NaMCu showed very little exfoliation after cycling to 0.8 V. 100 nm scale bar.

Figure 16. Scanning electron micrograph of a NaNMCo particle after water exposure.

2.4.5 Electrochemical Impedance Spectroscopy

EIS was used to characterize the changes in the charge transfer resistance and diffusion coefficient of the electrodes after electrochemical cycling to 0.8 V. To quantify these terms, the impedance results were modeled with the equivalent circuit in Figure 17, where:

• Rs represents the electrolyte solution resistance

• The first parallel circuit, consisting of CPE1 and R1, represents the high frequency

capacitance and resistance, respectively. CPE is a frequency-dependent constant-phase

element (퐶푃퐸 = [퐵(푗휔)푛]−1); B and n (0 < n < 1) are frequency-independent constants.

• The second parallel circuit is a Randles-type circuit which represents the lower frequency

impedance associated with bulk ion intercalation. It consists of a constant phase element

(CPE2), a charge-transfer resistance (Rct), and a Warburg element (Zw) that represents the

퐶 impedance associated with ion diffusion in the solid state (푍 = ). 푤 √푗휔

Figure 18a and b show the Nyquist plots of NaNMCo and NaMCu cycled to 0.8 V, where the markers indicate the measured data points and the lines represent the equivalent circuit

model fit. The slopes of the lines in Figure 18c and d were used to calculate the Na+ diffusion coefficient:

푅2푇2 퐷 = 2퐴2푛2퐹4퐶2휎2

where D is the diffusion coefficient (cm2 s-1), R is the gas constant, T is the temperature,

A is the area of the electrode, n is the number of electrons transferred per ion intercalated, F is the Faraday constant, C is the ion concentration, and σ is the slope of the real component of the impedance [Re(z)] vs. ω-1/2.201 Table VI shows the calculated results.

Figure 17. Equivalent circuit used for modeling the EIS results.

Table VI. Calculated values for Rs, Rct, and D for NaNMCo and NaMCu before and after cycling to 0.8 V vs. Ag/AgCl.

NaNMCo NaMCu

2 -1 2 -1 Cycle Number Rs (Ω) Rct (Ω) D (cm s ) Rs (Ω) Rct (Ω) D (cm s )

0 0.45 27 4.97 x 10-7 0.82 12 4.10 x 10-7

10 0.44 39 1.67 x 10-8 0.80 34 6.00 x 10-8

Figure 18. EIS results of NaNMCo and NaMCu before and after cycling to 0.8 V for 10 cycles at

0.5 mV s-1. a) Nyquist plot of NaNMCo and b) NaMCu showing a large increase in charge transfer resistance after cycling. Real impedance [Re(z)] vs. ω-1/2 for c) NaNMCo and d) NaMCu before and after cycling, where the slope of the linear region was used in the calculation of the diffusion coefficient.

The capacity decline of the NaMCu cycled to 0.8 V is likely due to an increase in the charge transfer resistance (Table VI). The mechanism of capacity fade in NaMCu cycled to 0.8 V is likely similar to its behavior in non-aqueous electrolytes, which showed no significant changes in the

XRD patterns before and after cycling even though there was a systematic decrease of redox peak

intensities during electrochemical cycling.165 While cycling to 1.1 V improved the capacity of

NaMCu, the EIS results showed a large increase in the charge transfer resistance after the first 10 cycles (Fig. 18). In the case of NaNMCo, which transformed to a birnessite phase and had significant particle exfoliation, Table VI shows that the diffusion coefficient decreased and the charge transfer resistance increased after the first 10 cycles. This suggests that Na+ diffusion within the NaNMCo was impeded either by the structural disorder after water intercalation, or by the interlayer water itself. While the water may act as a diffusion barrier, the particle damage from water intercalation shown in Figure 15b, c, and f indicates that particle exfoliation and fracture also contributed to the rise in impedance, and especially charge transfer resistance, after cycling.

2.5 Conclusions

This study establishes the interlayer chemistry and charge storage mechanism of P2 layered

Na+ oxides in aqueous electrolytes. At a critical interlayer Na+ content (~ 0.4 Na+ per formula unit), water intercalates into the materials which leads to formation of a birnessite-like layered structure and severe exfoliation of the particles. The potential at which the critical Na+ content is reached is controlled by the redox potential of the oxides, which is in turn determined by the transition metal composition. While these P2 oxides experience a large capacity loss due to the transformation to a birnessite-like phase, their first cycle capacities are comparable to those obtained with non-aqueous electrolytes. Decreasing the particle size of the P2 oxides may enable higher capacity retention by allowing the particles to expand and contract more uniformly during cycling, while maintaining good contact within the composite electrode. Additionally, this type of electrochemically-induced exfoliation process may be useful for synthesis of nanosheets of these materials. Overall, this work provides fundamental understanding of the effects of the transition metal composition on the aqueous interlayer chemistry and electrochemical activity of manganese-

rich P2 layered Na+ oxides, which are of interest for aqueous Na+ energy storage and desalination applications.

2.6 Conflict of Interest

There are no conflicts of interest to declare.

2.7 Acknowledgements

The authors thank Ruocun (John) Wang for assistance with TGA. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. 571800 (to S. B.). V.A. acknowledges start-up funding support from North

Carolina State University and the University Global Partnership Network. This work was performed in part at the Analytical Instrumentation Facility (AIF) at North Carolina State

University, which is supported by the State of North Carolina and the National Science Foundation

(award number ECCS-1542015). The AIF is a member of the North Carolina Research Triangle

NanotechnologyNetwork (RTNN), a site in the National Nanotechnology Coordinated

Infrastructure (NNCI).

CHAPTER 3

High Power Energy Storage via Electrochemically Expanded and Hydrated Manganese

Oxides

Preface

The work in this chapter is accepted for publication in Frontiers in Chemistry:

Electrochemistry as “High Power Energy Storage via Electrochemically Expanded and Hydrated

Manganese Oxides” by Shelby Boyd, Natalie R. Geise, Michael F. Toney, and Veronica Augustyn.

The previous chapter showed that P2 oxides are unsuitable for use as cathodes in aqueous electrolytes, as particle expansion upon water intercalation leads to electrode failure. In this work, we further investigate the implications of water intercalation into these micron-sized particles.

Many applications, from electric vehicles to smart grids, could benefit from electrochemical energy storage devices made with abundant materials and with high power densities.

Electrochemical capacitors are attractive for these applications because they have intermediate energy densities relative to batteries and dielectric capacitors, typically charge in a few seconds, and can last ~1,000,000 cycles. The most widely used approach to increase the capacitance of electrochemical capacitor electrodes is to increase their surface area. However, the high surface area of nanostructured materials leads to low volumetric capacitance and increases the potential for parasitic reactions with the electrolyte. In this work, we present a scalable strategy for producing micron-scale hydrated manganese oxide particles that exhibit capacitive behavior and a greater volumetric capacitance than commercially available activated carbon at charge/discharge timescales of up to 40 seconds. These results demonstrate that bulk layered materials can be engineered into effective electrochemical capacitor electrodes by controlling the interlayer chemistry to enable particle expansion and interlayer hydration.

3.1 Abstract

Understanding the materials design features that lead to high power electrochemical energy storage is important for applications from electric vehicles to smart grids. Electrochemical capacitors offer a highly attractive solution for these applications, with energy and power densities between those of batteries and dielectric capacitors. To date, the most common approach to increase the capacitance of electrochemical capacitor materials is to increase their surface area by nanostructuring. However, nanostructured materials have several drawbacks including lower volumetric capacitance. In this work, we present a scalable “top-down” strategy for the synthesis of EC electrode materials by electrochemically expanding micron-scale high temperature-derived layered sodium manganese oxides. We hypothesize that the electrochemical expansion induces two changes to the oxide that result in a promising electrochemical capacitor material: (1) interlayer hydration, which improves the interlayer diffusion kinetics and buffers intercalation- induced structural changes, and (2) particle expansion, which significantly improves electrode integrity and volumetric capacitance. When compared with a commercially available activated carbon for electrochemical capacitors, the expanded materials have higher volumetric capacitance at charge/discharge timescales of up to 40 seconds. This shows that expanded and hydrated manganese-based oxide powders are viable candidates for electrochemical capacitor electrodes.

3.2 Introduction

Electrochemical energy storage plays ever-increasing roles in our daily lives by powering everything from portable electronics to electric vehicles. Electrochemical capacitors (ECs) are a class of energy storage devices with intermediate energy and power between those of batteries and dielectric capacitors. Commercialized ECs are highly attractive for diverse applications requiring

reliability, large currents, and high energy efficiency. They exhibit specific energy of up to 10

Wh/kg, specific power of up to 30 kW/kg, typical charge/discharge timescales on the order of seconds, and lifetimes of up to ~ 1,000,000 cycles.22,36 Most commercialized ECs store energy by the rapid (within seconds) formation of the electric double layer (EDLC) at the electrode/electrolyte interface. This mechanism can give rise to specific capacitance values of up to 150 F/g when the electrolyte ion size matches the average pore size of the electrode material.202

Another capacitive energy storage mechanism, termed pseudocapacitance, uses fast and reversible redox reactions in materials such as transition metal oxides and can lead to capacitances > 150

F/g.203

Increasing the energy density and reducing the cost of ECs require the development of new electrode materials that exhibit high energy storage performance and are made from abundant elements via scalable synthesis processes. Thus far, the search for new EC materials has primarily focused on the synthesis of nanostructured materials. This improves the power density by increasing the interfacial area between the electrode and electrolyte, and reducing the solid-state diffusion distance within the particles.42,44,204,205 However, the high surface area of nanostructured particles can lead to undesirably low volumetric capacitance electrodes and increased parasitic side reactions with the electrolyte.206,207 Therefore, there is a need for high-power energy storage materials that match the rate performance of high surface area materials but exhibit higher volumetric capacitance, as well as scalable strategies to synthesize such materials.

Commonly studied materials for ECs include transition metal oxides with hydrated interlayers. Oxides such as V2O5·xH2O, WO3·2H2O, and birnessite (typical formula

KxMnO2·nH2O) show pseudocapacitive behavior in aqueous electrolytes due to reversible cation intercalation.15,178,181,194,208,209 The interlayer water in these materials is hypothesized to enable fast

energy storage by buffering structural changes during cycling, reducing transition metal dissolution into the electrolyte, and/or improving the interlayer diffusion kinetics of intercalating cations. 20,208,210 In particular, birnessite manganese oxides are promising EC materials due to the abundance and safety of manganese. However, their low crystallinity and commonly nanoscale particles result in low material utilization and therefore low volumetric capacitance in thick electrodes.96 Developing material synthesis techniques to produce micron-scale transition metal oxide particles with hydrated interlayers could lead to high volumetric capacitance EC electrodes.

To address this, we propose the use of electrochemically expanded and hydrated manganese oxides based on P2 oxides of the formula Na0.67MO2. Here, M is a combination of manganese and other transition metals and P2 indicates the prismatic (P) coordination of Na+ and

…ABBA… stacking of the oxygen layers. The high temperature (~ 900°C) synthesis of the P2

2 211 oxides leads to micron-scale primary particles with surface areas of ~ 1 m /g. P2 Na0.67MO2 are widely studied for non-aqueous sodium ion battery cathodes, but often exhibit poor cyclability due to the Jahn-Teller distortion and dissolution of the Mn atoms during electrochemical cycling, and poor electronic and ionic conductivity.19,194,212,213 However, these materials could be promising as

EC electrode materials due to their tendency to form hydrated phases under ambient conditions.137,140,214 In our previous work, we established that these structures are also susceptible to water intercalation upon electrochemical cycling in aqueous electrolytes.214 This causes a 25% c-axis expansion and a phase transformation to a birnessite-like structure that exhibits capacitive electrochemical behavior. However, the large structural change causes particle detachment from the electrode, which results in severe capacity decline. The capacitive response of the expanded, hydrated oxide led us to consider whether it was possible to perform the expansion prior to electrode assembly. The resulting expanded micron-sized particles of manganese-based oxide with

hydrated interlayers could then be used for high rate capability and high volumetric energy density

EC electrodes with improved stability upon extended cycling.

In this work, we present a scalable “top-down” strategy for the synthesis of EC electrode materials by electrochemically expanding micron-scale high temperature-derived layered manganese oxides. The batch process was inspired by the electrochemical exfoliation methods

166–168 developed for large sheet graphite and MoS2. Assembly of the expanded materials into electrodes leads to high power capacitive energy storage. Comparison with commercial activated carbon shows that the oxides exhibit similar rate capability but higher volumetric capacitance. We intended to also compare these materials to crystalline nanomaterials, but ran into difficulties detailed in Appendix A. We hypothesize that the electrochemical expansion enables high power and high volumetric capacitance via two important changes in the oxide: (1) interlayer hydration, which improves interlayer diffusion kinetics while also buffering intercalation-induced structural changes, and (2) particle expansion, which significantly improves electrode integrity and volumetric capacitance.

3.3 Materials and Methods

3.3.1 Materials Synthesis: Bulk Powders

A coprecipitation and calcination method was used to prepare the micron-scale layered

214 oxide powders with a P2 structure. Briefly, a 2:1 ratio of Mn(CH2CHOO)2·4H2O and

Cu(CH2CHOO)2 (Alfa Aesar) were dissolved in deionized water, and added at ~ 1 drop/s into a stirred aqueous NaOH (Fisher Scientific) solution of pH ~12. After aging for ~1 hour, the

Mn0.62Cu0.31(OH)2 precipitate was washed until pH neutral, filtered, and dried overnight at 120 °C.

The hydroxide precursor was ball milled in ethanol for 24 hours. After drying the material again,

+ + Na was added in a 0.74 : 1 molar ratio of Na : MCu(OH)2 by mixing the precursor and NaOH in

DI water for 1 hour at room temperature and then heating it at 100 °C on a stir plate until dry. The dried powder was ground with a mortar and pestle to break up any large chunks, and annealed at

500 °C for 5 hours. After cooling to room temperature, the powder was ground for 15 minutes before calcination at 850 °C for 6 hours and subsequent transfer to an inert-atmosphere glovebox

(< 1 ppm H2O and O2) while at ~70 °C. The calcined powder was ground with a mortar and pestle for 30 minutes in the glovebox. The composition of the as-synthesized material was

Na0.64Mn0.62Cu0.31O2, abbreviated NaMCu. A Ni-containing material, Na0.64Ni0.22Mn0.66Cu0.12O2

(NaNMCu), was synthesized in the same manner.

3.3.2 Materials Synthesis: Electrochemical Expansion

To electrochemically expand and hydrate the P2 powders, ~ 0.5 g of the material was placed into an electrolyte-permeable and electronically-connected pouch acting as the positive electrode in a two electrode cell, vs. a Ni foam negative electrode. The pouch was made by folding double-layer dialysis tubing (Thermo Scientific SnakeSkin®, 10,000 MWCO, 22 mm diameter) around a coiled Pt wire electrode (Pine Instruments, 99.99% pure) and sealing it with parafilm

(Fig. 1). The dialysis tubing held the NaMCu powder near (and optimally in contact with) the Pt wire. After ensuring that the 0.5 M K2SO4 (Fisher Scientific) electrolyte fully wet the dialysis tubing, +4 V was applied to the cell for 24 hours. After expansion, the pouch was rinsed and cut open. The expanded material was washed out of the pouch using DI water, and centrifuged at 4500

RPM for 3-5 minutes to remove excess water. The powders were rinsed at least twice more to remove all electrolyte salt, and centrifuged after each rinse. Finally, the expanded powder was air dried at room temperature.

Figure 1. Fabrication of the expansion pouch. (A) Dialysis tubing folded over on itself to form a double-layer wall, with one end folded into a point to thread through the Pt wire coil. (B) The threaded dialysis tubing with parafilm securing the folded end to the Pt wire. (C) After folding the tubing over the Pt wire and filling the pouch with P2 NaMCu powder, parafilm secures the outer wall of the pouch as well.

3.3.3 Methods: Synchrotron X-ray Diffraction

Synchrotron X-ray diffraction (XRD) was performed at the Stanford Synchrotron

Radiation Lightsource (SSRL) on beamline 7-2 with a 14.013 keV beam. The operando diffraction patterns were collected with a Pilatus 300K area detector (DECTRIS Ltd.) in portrait mode, in a

Bragg-Brentano ( - 2) reflection geometry at a sample-to-detector distance of 750 mm. XRD patterns were taken with the middle of the detector at 11.4 and 23.0 °2θ with a 3-second exposure every 20 seconds while cycling the electrode at 0.5 mV/s. After calibrating the detector geometry

(tilts and distance) with LaB6, the area diffraction patterns were reduced to one dimensional intensity vs. 2θ patterns with the pyFAI library.215 The electrochemical cell consisted of a 1 M

Na2SO4 (Fisher Scientific) electrolyte, a Pt counter electrode, and a miniature leakless Ag/AgCl reference electrode (eDAQ ET072-1) using a cell developed for in situ electrochemical X-ray scattering.179,216 The preparation of the working electrode is discussed in more detail in Section

2.5. Briefly, an 8 : 1 : 1 slurry of the P2 oxide, acetylene black, and polyvinylidene fluoride was

prepared in n-methyl pyrrolidone, cast onto a plasma-cleaned platinized silicon substrate (MTI

Corp.), and dried at 120 °C overnight.

3.3.4 Methods: Physical Characterization

XRD was used to determine the structure of the as-synthesized P2 and expanded powders, and the electrodes before and after electrochemical cycling. XRD was performed with standard

Bragg-Brentano geometry and Cu-K푎 radiation (PANalytical Empyrean). The powder samples were rotated at 7.5 RPM, while the electrodes remained stationary. Scanning electron microscopy

(SEM, FEI Verios 460L) was used to determine the morphology of the P2 powders before and after expansion, as well as after electrochemical cycling. The water content of the expanded samples was measured with thermogravimetric analysis (TGA; SII EXSTAR6000 TG/DTA6200), using aluminum pans to hold ~12 mg of powder, and heating in air at 5 °C /min from 25-300 °C.

3.3.5 Methods: Electrochemical Characterization

Electrode Preparation: The electrochemical behavior of the expanded particles was characterized using slurry electrodes cast onto either Ti mesh or foil (Alfa Aesar). The metal substrates were cleaned by sonication in ethanol, after which the mesh electrodes were dried and coated with slurry. The working face of the Ti foil was etched with sandpaper to improve slurry adhesion while the back of the foil electrode was covered with Kapton tape to minimize its current contribution during electrochemical cycling. The electrode was then plasma cleaned (Harrick

Plasma PDC-32G) for 3 minutes also to improve slurry adhesion.

The slurry composition varied depending on the type of current collector (mesh or foil).

We found that for the expanded oxide on Ti mesh, a slurry composition of 80 wt% active material,

17.5 wt% acetylene black (Alfa Aesar), and 2.5 wt% polyvinylidene fluoride (PVDF, Arkema

Kynar KV 900) gave good adhesion to the mesh and the best rate capability. The acetylene black slurries, used to understand the current contribution from the conductive carbon additive, consisted of 67 wt% acetylene black and 33 wt% PVDF. To compare the electrochemically expanded

NaMCu to commercial activated carbon on a volumetric basis, we used foil current collectors. For the activated carbon slurry on Ti foil, 90 wt% YP50 activated carbon (Kuraray Co., Ltd.) was combined with 10 wt% PVDF. The expanded oxide slurry on Ti foil consisted of 80 wt% active material, 15 wt% acetylene black, and 5 wt% PVDF. The dry components of each slurry were ground for 5 minutes before adding n-methyl pyrrolidone (NMP; Sigma Aldrich) and stirring overnight on a magnetic stir plate at 990 RPM. After painting the slurry onto the current collector, the electrodes dried for several hours at room temperature in the fume hood. At this point, the foil electrodes were placed between a folded weigh paper and calendared to the approximate thickness of the electrode-weigh paper assembly with a rolling mill (Durston) before transfer to an oven at

120 °C. We transferred the mesh electrodes directly from the fume hood to the oven at 120 °C, where they dried for several hours before calendaring to 125 µm between the sheets of a folded weigh paper. The final thickness of the mesh electrodes was approximately 90 µm.

Electrochemistry: All electrodes were tested with a three-electrode set up in glass 50 mL round bottom flasks with an aqueous 0.5 M K2SO4 (Fisher Scientific) electrolyte, using an

Ag/AgCl in 3.5 M KCl reference electrode (Pine Instruments) and a platinum wire counter electrode (99.997%, Alfa Aesar). All tests used Ni-plated stainless steel alligator clips to hold the working and counter electrodes in the electrolyte. The cyclic voltammetry was performed with a

Biologic MPG2 potentiostat. Electrochemical data was analyzed using Matlab code (Appendix B).

3.4 Results and Discussion

3.4.1 Mechanism of Electrochemical Expansion

To determine the mechanism of electrochemical expansion and interlayer hydration of P2- type layered sodium manganese oxides in aqueous electrolytes, we performed operando XRD during cyclic voltammetry of NaMCu and NaNMCu. The crystal structure of a P2-type layered oxide (Fig. 2) consists of layers of edge-sharing MO6 octahedra, and ~67% of the interlayer prismatic sites are filled with Na+.151

Figure 2. The P2 structure of the pristine material, showing the edge-sharing MO6 octahedra forming layers with … ABBA … oxygen stacking, where M represents Mn and other transition metals. The Na+ are located in two types of trigonal prismatic sites between the oxide layers.

Figure 3A shows the cyclic voltammogram (CV) of NaMCu at 0.5 mV/s in 1 M Na2SO4, while Figure 3B shows the water insertion mechanism proposed in our previous work.214 During the first anodic cycle, the CV of NaMCu shows current peaks around 0.2 and 0.9 V vs. Ag/AgCl.

On the subsequent cathodic scan, the overall current decreases and is relatively constant as a

function of potential. These electrochemical changes suggest a change in energy storage mechanism in the material. Well-defined current peaks correlate to a well-defined Gibbs free energy of reaction, which in an intercalation-type material indicates little dispersion in the intercalation site energy. On the other hand, constant current as a function of potential is indicative of a capacitive mechanism exhibited by many manganese oxides in neutral pH electrolytes.85,217,218

Figure 3. Mechanism of water intercalation into P2-type NaMCu upon electrochemical cycling in

1 M Na2SO4. (A) Cyclic voltammetry at 0.5 mV/s. A.B. indicates “acetylene black,” the electrochemical response of the conductive carbon in the electrode. (B) Cartoon showing the insertion of water molecules (red) from the electrolyte into the material interlayer to compensate for the electrochemical de-intercalation of Na+ (dark blue).

The structural changes of NaMCu during the first two CV cycles were measured with operando synchrotron XRD (Fig. 4). Two changes are apparent: the appearance of a new peak during the first anodic cycle (discussed below) and shift of the NaMCu diffraction peak. The interlayer spacing of the P2 phase, indicated by the (002) peak at ~9 °2θ, increases from 5.59 Å

(9.07 °2θ) at 0 V to 5.65 Å (8.97 °2θ) at 1.1 V. Upon reduction to 0 V, the spacing returns to nearly its original value, 5.61 Å (9.04 °2θ). This shows that the interlayer spacing reversibly increases

during oxidation and decreases during reduction. The continuous change of the NaMCu interlayer spacing as a function of potential indicates a solid-solution intercalation mechanism, similar to its structural behavior in non-aqueous Na+ electrolytes.164,165,219 The faint splitting of the P2 (001) peak near the end of the cathodic cycle may indicate that the remaining P2 material forms two phases with slightly different Na+ content.

In addition to this expected behavior, the appearance of a new peak at 7.19 °2θ at ~ 0.9 V during the first anodic cycle indicates the formation of a new phase. According to prior results, this peak corresponds to the (001) plane of a birnessite-like hydrated phase with an interlayer spacing of 7.05 Å.137,140,191,214,220 The full XRD patterns of the material before and after the phase transformation are shown in Figure 4B. The large interlayer spacing of the new phase indicates the insertion of a single layer of water molecules from the aqueous electrolyte into the interlayer of NaMCu.180,194 Moreover, reversible peak shifts indicate that this new hydrated phase is electrochemically active: upon reduction from 1.1 V to 0 V, the interlayer spacing decreases to

6.97 Å (7.27 °2θ). During the second cycle it increases to 7.07 Å (7.17 °2θ) at 1.1V and shifts back to 6.97 Å (7.27 °2θ) at 0 V. This change of ~ 0.1 Å is about half of that typically observed in birnessite in aqueous electrolytes.15,218 The reversible peak shifts of the hydrated phase indicate that pseudocapacitance associated with cation (de)intercalation into the hydrated interlayer at least partially contributes to the capacitive energy storage mechanism. These changes would not appear if the capacitive behavior was simply due to the formation of the double layer at the outer surface of the particles. The intensity increase of the hydrated phase peak and corresponding decrease in the P2 (002) peak during the first anodic sweep show the partial phase transformation of the electrode material. However, all peak intensities decrease after ~ 0.5 V during the second cathodic

sweep, as the change in particle volume causes the electrode to delaminate from the current collector.

Figure 4. Structural changes of P2 NaMCu upon electrochemical cycling (A) Operando synchrotron XRD during the first two CV cycles at 0.5 mV/s. The right-most panel shows the applied potential (dashed line) and the current response (solid line). During the first anodic cycle, the interlayer peak of the hydrated birnessite-like phase (~7 °2θ) emerges around 0.9 V. Both the

P2 and the hydrated peak show reversible, continuous changes in the interlayer spacing as a function of potential attributed to Na+ de/intercalation. The peak at 8.1 °2θ is due to the electrochemical cell. (B) XRD pattern of the pristine NaMCu powder (“NaMCu”), where the (002) peak indicates the interlayer spacing. Post-electrochemistry, the NaMCu transforms to a hydrated structure. The substrate peaks of the Ti current collector are indicated by •. In situ XRD image courtesy of Natalie Geise.

Figure 5 shows similar behavior in a P2 oxide with a different composition, NaNMCu, where the inclusion of nickel led to Na+ deintercalation and the subsequent formation of the birnessite-like phase at a lower potential.164,165,221 Overall, the operando results show that when

these P2 oxides are cycled in an aqueous electrolyte, water incorporation occurs during Na+ deintercalation, likely to offset the increasing electrostatic repulsion between the transition metal and oxygen layers. Within an individual particle, the formation of this birnessite-like phase may lead to the capacitive CV observed after the first cycle. However, the large expansion of the P2 particles (25 % c-axis increase) in the slurry electrode leads to loss of electronic connection to the current collector, or even delamination, when cast onto the electrode before expansion. If the electrochemical expansion is better controlled, the formation of micron-scale particles with hydrated interlayers with a capacitive electrochemical response indicates that these particles could be viable for high volumetric capacitance EC materials.

Figure 5. Operando synchrotron XRD of NaNMCu, showing the P2 (002) peak ~ 9.11 °2θ, which decreases with material oxidation and Na+ extraction up to 0.8 V, and returns to its original position upon reduction to 0 V. This material also experiences the emergence of the hydrated phase at ~

7.23 °2θ, which continuously contracts (expands) during reduction (oxidation) due to interlayer cation intercalation (deintercalation). Both phases remain electrochemically active during the second cycle, showing reversible interlayer spacing changes. In situ XRD image courtesy of

Natalie Geise.

3.4.2 Batch Expansion Process

To circumvent the electrical contact and slurry delamination problems resulting from in situ P2 particle expansion on electrodes, we developed a batch expansion process for the P2 oxide powder, as described in the experimental section. Figure 6 shows the expansion cell, along with scanning electron microscopy (SEM) images of a P2 particle (Fig. 6A) and an expanded particle

(Fig. 6C). The resulting expanded and hydrated particles can be assembled into electrodes, thus

bypassing the issue of direct electrochemical expansion leading to delamination. The batch process uses a neutral pH electrolyte, a voltage source, permeable membrane, and a Ni foam counter electrode, rendering it environmentally friendly and scalable. Figure 7 shows representative chronoamperometry for the process. We observed that a smoother current response is a good indicator of expansion quality —noisier curves resulted in less expansion of the P2 oxide, as indicated by XRD (Fig. 8A). This is likely due to variable electrical contact between the powder and the Pt coil in the pouch cell, which could be improved with more advanced pouch designs.

Figure 6. Effect of batch expansion on particle morphology: (A) a pristine P2 NaMCu particle has a compact structure. (B) A schematic of the electrochemical expansion setup, where the P2 material is contained in a dialysis tubing pouch around a coil of Pt wire, and the counter electrode is Ni foam. (C) A typical fully expanded NaMCu particle, which retains its ab-plane morphology but expands vertically due to water insertion. Scale bar 2 μm.

Figure 7. Chronoamperometric expansion of the fully (dark green; F.E.) and partially (light green;

P.E.) expanded materials. The “noise” of each curve could be related to the electronic contact of particles within the pouch that determines the extent of electrochemical expansion.

3.4.3 Structural Characterization of Expanded Materials

To understand the effect of the batch expansion process on the structural and electrochemical performance, we compared three structures: as-synthesized NaMCu, fully expanded (F.E.) NaMCu, and partially expanded (P.E.) NaMCu. Figure 8 shows the XRD, TGA, and SEM of these materials. The pristine NaMCu has the same structure as reported previously

214: a primary P2-type phase (*) and a small amount of CuO (+). The first peak at 15.92 °2θ (5.57

Å) corresponds to the (002) peak of the P2 phase. The F.E. NaMCu shows a completely expanded and hydrated structure: the P2-phase is no longer present and the interlayer peak at 12.99 °2θ (6.99

Å) indicates a 25% expansion, the same as the operando XRD experiments. As discussed above, the large increase in interlayer spacing is due to the transformation to a new hydrated phase. Both the P2 and F.E. NaMCu materials exhibit a peak at 35.8 °2θ (2.5 Å). This peak corresponds to the

(100) plane of the P2 structure, and its presence in both the pristine and F.E. materials indicates that the lattice spacing along the transition metal oxide sheets is unaffected by electrochemical expansion. The larger c-axis in the expanded materials leads to slightly decreased angles of the

(101) and (102) peaks at 36.5 and 38.1 °2θ. The two-phase P.E. structure indicates that the expansion proceeds via a direct phase transformation. This agrees with the operando XRD, which shows the emergence of the hydrated phase at a distinct potential as opposed to a gradual structural transition over a broad potential range.

Figure 8. Structural characterization of expanded NaMCu materials. (A) Powder XRD shows the complete transformation of the F.E. material into the hydrated phase, while the P.E. material contains both the hydrated phase and residual P2 phase. (B) TGA shows that both F.E. and P.E.

NaMCu materials lose a significant amount of water with increasing temperature. SEM of the (C) pristine NaMCu powder and (D) F.E. NaMCu powder shows that the expanded particles retain their initial hexagonal morphology and particle size but are now expanded along the layers. Scale bar 3 µm.

TGA of each material indicates decreasing mass loss between room temperature (~ 25 °C) and 300 °C in the order F.E. NaMCu > P.E. NaMCu > NaMCu. In this temperature range, mass

losses are most likely due to the removal of water molecules from the oxide surface and interlayer.

The composition of the F.E. material for TGA was Mn0.62Cu0.31O2·xH2O, assuming the removal of all Na+ during electrochemical expansion. This means that the 6.2 wt% lost from F.E. NaMCu between 50 and 120 °C corresponds to 0.33 mol H2O per MCu (x = 0.33). Many birnessites also have a oxide: water content ratio near 1 : 0.33, supporting the XRD data that electrochemical expansion leads to insertion of a single layer of water molecules into the interlayer of the P2 oxides.

The P.E. NaMCu lost 2.4 wt%, which suggests only ~ 38 % of the powder expanded based on the mass lost from F.E. NaMCu. Lastly, NaMCu exhibits only a minor 1.2 wt% loss, likely due to the desorption of surface water.

The SEM images in Figure 8C and D show that the morphology change is due to the crystallographic change: the ab plane particle size and shape are retained after expansion, while the c-axis dimensions increase as the layers experience varying degrees of partial exfoliation.

Figure 6 shows higher magnification SEM images of pristine and expanded NaMCu particles.

Before expansion, the material consists of dense, roughly hexagonal, micron-scale primary particles. Based on the crystal structure, the interlayer spacing is parallel to the surface of hexagon- like primary particles. After electrochemical oxidation, there is clear partial exfoliation of the particles along the c axis that gives rise to large pores hundreds of nanometers in dimension. We hypothesize that the large pores and interlayer hydration formed by the expansion process both enable high power energy storage.

3.4.4 Electrochemical Behavior of Expanded Materials

We characterized the electrochemical behavior of pristine, P.E., and F.E. NaMCu in a 0.5

+ M K2SO4 electrolyte. This electrolyte was selected over Na2SO4 because K has a smaller hydrated

ion radius compared to Na+, which is hypothesized to allow higher rate capability and cyclability in aqueous electrolytes.15,222–224 Figure 9 shows the CVs of the pristine, P.E., and F.E. NaMCu in

0.5 M K2SO4 at 1, 10, and 100 mV/s. The response of the acetylene black conductive additive is also shown for reference. It contributes only minimal double-layer current. The F.E. NaMCu exhibits a capacitive CV at 1 and 10 mV/s, with a semi-rectangular shape and broad peaks similar to those often observed in birnessite.15,220 The P.E. NaMCu also has a semi-rectangular CV, albeit with a lower specific current and lacking the broad peaks present in the F.E. material. In contrast, the pristine P2 NaMCu particles expand upon intercalating water during the first anodic cycle, and the electrode capacity drops significantly as the 25% increase along the c-axis causes particles to delaminate. P2 NaMCu electrodes do not show clear redox peaks in K2SO4 (Fig. 10), possibly

+ + because the interlayer Na partially exchanges with K and H2O immediately upon immersion into the electrolyte. The semi-rectangular CV, with the lowest specific current of the three electrodes, is likely from the response of the remaining, partially-hydrated material that is still in electrical contact with the current collector. By 100 mV/s, all three materials exhibit significant polarization arising from increased Ohmic resistance from the large measured currents. Overall, these results show that the degree of expansion directly determines the material’s electrochemical behavior, and that electrochemical expansion before electrode assembly leads to stable, capacitive energy storage.

Figure 9. CVs of the pristine P2, P.E., and F.E. NaMCu materials in 0.5 M K2SO4 electrolyte at

(A) 1 mV/s, (B) 10 mV/s, and (C) 100 mV/s. The specific current from just the acetylene black

(A.B.) conductive additive is shown for reference.

Figure 10. Cyclic voltammograms of the first cycle of pristine NaMCu mesh electrodes in Na2SO4

(dotted line) and K2SO4 (solid line) aqueous electrolytes at 0.1 mV/s. Here, the two primary redox peaks of NaMCu in Na2SO4 occur before 0.8 V vs. Ag/AgCl. Since the hydrated phase in Figure

1 appears around 0.9 V, this suggests that completion of the redox reactions associated with the two anodic redox peaks leads to the intercalation of water and subsequent material expansion.

Figure 11 shows the cathodic capacitance and rate capability of the three materials. The highest capacitance of 102 F/g (23 mAh/g) is obtained with the F.E. materials. This value is comparable to capacitances of activated carbon materials, which is surprising given that the surface area of the oxide materials is much smaller. When cycled from 0.1 to 50 mV/s, the F.E. NaMCu retains 34% of its initial capacitance. The maximum capacitance of the P.E. NaMCu is lower, 62.4

F/g (14 mAh/g), but its rate capability is slightly better than that of F.E. NaMCu. The pristine P2

NaMCu undergoes electrochemical expansion and hydration directly on the electrode. Its second- cycle capacitance of 57 F/g (13 mAh/g) drops off significantly as the material delaminates from the electrode. Ex situ XRD (Fig. 11C) indicates that F.E. and P.E. NaMCu retain their initial structure after electrochemical cycling. There is no ex situ XRD of the P2 electrodes after electrochemistry because the slurries delaminated from the current collectors during cycling.

Together, these results show that the F.E. and P.E. NaMCu exhibit relatively high capacitance and rate capability for aqueous energy storage due to the hydrated interlayer and particle expansion.

The batch electrochemical expansion of P2 NaMCu and subsequent electrode assembly leads to electrodes with high rate capability and is promising for high-power energy storage.

Figure 11. Electrochemical energy storage rate capability and post-electrochemical cycling material structure. (A) Cathodic capacitance and (B) rate capability (cathodic capacitance normalized to the capacitance at 0.1 mV/s), from 0.1 to 100 mV/s. The low capacity and rate capability of the acetylene black (A.B.) conductive additive shows that the capacitive electrochemical response is due to the oxide active materials. (C) Ex situ XRD of electrodes after electrochemical cycling shows that the F.E. and P.E. retain their initial structures.

Evaluation of the cyclability of the three oxide materials shows that the F.E. NaMCu electrode retained its structure and the most capacity after 600 cycles at 10 mV/s (Fig. 12), while the P.E. NaMCu converted to the F.E. structure and the P2 NaMCu delaminated from the electrode.

The initial capacitances were 58 F/g (13 mAh/g) for the F.E. electrode, 34 F/g (8 mAh/g) for the

P.E. electrode, and 37 F/g (8 mAh/g) for the P2 electrode. After 600 cycles at 10 mV/s, the F.E. electrode retained 86.3% capacity, the P.E. retained 85.7%, and the P2 retained 40.4%. Figure 6 shows that the F.E. electrode experienced an initial capacity drop, but after 60 cycles the capacity increased close to is initial value. The P.E. electrode experienced a steady capacity increase over the first 50 cycles, and then a steady decline during the subsequent 550. The P2 NaMCu lost most of its capacity within the first 50 cycles, as water insertion into the P2 NaMCu partially expanded the oxide particles, causing them to fall off the electrode due to the change in volume.

Figure 12. (A) Cycling stability of F.E., P.E., and P2 NaMCu over 600 cycles at 10 mV/s. (B) Ex situ XRD after 600 cycles shows that the F.E. NaMCu retains the hydrated phase, while some of the remaining P2 material in the P.E. NaMCu electrode expanded after prolonged cycling.

XRD of the F.E. and P.E. NaMCu after the cyclability testing (Fig. 6B) shows that the F.E. phase is stable under these electrochemical conditions. This suggests that the particle expansion and interlayer hydration limit further structural changes in the material, leading to better stability.

Figure 6B shows that initially unexpanded P2 material into P.E. electrode also transforms to the expanded phase after cycling. It appears that the initial fraction of expanded particles was enough to maintain electronic connectivity with the particles expanded in situ. Slurry delamination during cycling prevented ex situ post-cycling XRD of the pristine NaMCu, but our previous work showed that after 50 cycles, NaMCu partially transformed to the hydrated phase.214.

Post-electrochemical SEM (Fig. 13) shows that while most particles in the F.E. and P.E. electrodes retained their original morphology, some exhibit a nanostructured surface coating. After

600 cycles, the morphology of the F.E. NaMCu primary particles appears similar as before cycling.

However, the surface of these primary particles now has a nano–structured, semi-porous coating.

One possible mechanism of this surface coating could be restructuring due to the dissolution of

Mn2+ during reduction, and subsequent re-deposition during oxidation.225 The variability of this 89

surface coating from particle to particle in F.E. NaMCu may highlight how the electrode architecture affects the relevant electrochemical reaction. A well-connected particle may experience more overall charge transfer, leading to surface restructuring. However, there was little surface coating in the P.E. NaMCu, suggesting that more of the current may have gone into expanding the remaining P2 particles. Figure 13D shows one of the few P.E. NaMCu particles with partial surface coating. Finally, Figure 13E and 13F show the pristine P2 NaMCu after 600 cycles. While the P2 particles expanded somewhat, their morphology is much smoother than F.E. or P.E. electrode particles. Overall, the electrochemistry, XRD, and SEM results highlight that electrodes assembled from pre-expanded F.E. or P.E. NaMCu possess high rate capability and structure stability that make them suitable as EC materials.

Figure 13. SEM images of (A-B) F.E., (C-D) P.E., and (E-F) P2 NaMCu electrodes after 600 cycles in 0.5 M K2SO4. While most F.E. particles show expansion or a surface coating, few P.E. particles show surface coating, and few P2 particles even show expansion. Scale bar 500 nm.

3.4.5 Comparison of Expanded NaMCu to Commercial Activated Carbon

To test our hypothesis that the hydrated and expanded NaMCu would allow an increase in the volumetric capacitance of EC electrodes, we compared the P.E. NaMCu with a commercially available activated carbon used for EC electrodes. P.E. NaMCu was selected due to its better rate capability than F.E. NaMCu. To enable comparison of the volumetric capacity/capacitance, the materials were cast onto foil (vs. mesh) current collectors. Figure 14 compares the CVs for both materials at 1, 10, and 100 mV/s in 0.5 M K2SO4 while Figure 15 shows the specific capacity/capacitance and rate capability. Both P.E. NaMCu and activated carbon exhibit nearly rectangular, ideally capacitive CVs. At sweep rates up to 20 mV/s (corresponding to a charge/discharge time of 40 seconds), P.E. NaMCu shows a higher specific current than activated carbon, indicating that the expanded oxide particles give better volumetric performance than the high surface area activated carbon. At 0.1 mV/s, the volumetric capacitances of P.E. NaMCu and activated carbon are 57.2 F/cm3 (12.7 mAh/cm3) and 20.9 F/cm3 (4.64 mAh/cm3) respectively.

However, the response of the two materials becomes similar at faster sweep rates; by 100 mV/s the CVs essentially overlap and their diagonality indicates both are more Ohmically resistive. The similarity of the material response at faster sweep rates may be due to similar issues of maintaining adequate ionic and electronic conductivity in the electrodes. These results show that an oxide material with expanded and hydrated micron-size particles can increase EC energy density over traditionally used high surface area activated carbon at timescales of up to 40 seconds.

Figure 14. CV comparison of P.E. NaMCu and activated carbon (A.C.) on the basis of their specific current at (A) 1 mV/s, (B) 10 mV/s, and (C) 100 mV/s. At sweep rates up to ~ 20 mV/s, the P.E. NaMCu out-performs the activated carbon, although both electrodes appear relatively resistive at 100 mV/s.

Figure 15. (A) Volumetric capacity/capacitance and (B) rate capability of P.E. NaMCu and activated carbon (A.C.) electrodes.

3.5 Conclusions

This work describes how electrochemically expanding the particles and hydrating the interlayer of micron-sized layered oxides leads to EC electrodes with high volumetric capacitance and cyclability in aqueous electrolytes. The electrochemical expansion changes the electrochemical characteristics of the material from battery-like in the initial Na+ deintercalation to capacitive after expansion. Specifically, after interlayer hydration and subsequent particle expansion, micron-sized P2 oxide particles exhibit capacitive behavior that is at least in part pseudocapacitive, as evidenced by reversible interlayer spacing changes during operando XRD.

The obvious reduction in redox peaks in CVs after expansion suggests that the material deformation is further buffered by the interlayer water. In addition, the surface area of the bulk expanded particles is only slightly greater than that of the pristine materials. Therefore, we hypothesize that the interlayer expansion and hydration effectively increase the surface area by extending the electrolyte into the bulk of the particles in two ways. First, hydrating the material interlayer improves cation transfer from the bulk electrolyte to the particles, and second, the large

(~ 100 nm) pores between expanded sections of the material allow easier access of the bulk electrolyte to the particles. The hydrated interlayers may also cushion the structural effects of ion intercalation. All of these increase the rate at which electrolyte cations can approach transition metal oxide storage sites. These results show that hydrating the material interlayer allowed the micron-scale particles to maintain their structure during extended cycling, making them compatible for capacitive energy storage in aqueous electrolytes. By expanding the interlayer of

P2 NaMCu oxide, we show that particles with a large solid-state cation diffusion distance can be competitive with the state-of-the-art activated carbon for EC electrodes in aqueous electrolytes.

Overall, this shows that electrochemically-driven expansion of oxide materials can tune both the

interlayer chemistry and particle size, leading to a new scalable synthesis strategy for EC materials with high volumetric capacitance.

3.6 Acknowledgements

The authors thank Cynthia Koehler and Prof. Thom LaBean (NC State University) for providing dialysis tubing. S.B. was supported by the National Science Foundation Graduate

Research Fellowship Program under Grant No. 571800. N.R.G. was supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship

(NDSEG) Program. XRD and SEM studies were supported as part of the Fluid Interface Reactions,

Structures and Transport (FIRST) Center, an Energy Frontier Research Center funded by the U.S.

Department of Energy, Office of Science, Office of Basic Energy Sciences. This work was performed in part at the Analytical Instrumentation Facility (AIF) at North Carolina State

University, which is supported by the State of North Carolina and the National Science Foundation

(award number ECCS-1542015). The AIF is a member of the North Carolina Research Triangle

Nanotechnology Network (RTNN), a site in the National Nanotechnology Coordinated

Infrastructure (NNCI). Use of the Stanford Synchrotron Radiation Lightsource, SLAC National

Accelerator Laboratory, is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Contract No. DE-AC02-76SF00515.

3.7 Author Contributions Statement

SB and VA contributed to the study conception and design. All authors designed the synchrotron experiments. NRG extracted and analysed the synchrotron data. SB performed all

other experiments and performed the data analysis. All authors contributed to writing and revising the manuscript, and read and approved the submitted version.

3.8 Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

CHAPTER 4

Redox or Double Layer? Interlayer Confinement Blurs the Horizon Between Faradaic and

Non-Faradaic Charge Storage in Birnessite

4 Preface

This chapter focuses on the origin of capacitive behavior in layered manganese oxides in aqueous electrolytes. Chapters 2 and 3 focused on changing the interlayer chemistry of P2 oxides and observing the subsequent changes in behavior. We found that the intercalation of interlayer water led to more capacitive behavior, even in large oxide particles. However, these chapters did not investigate the origin of this improvement in performance. In this chapter, I use nanostructured birnessite as a model material to understand the origin of capacitive behavior in hydrated manganese-based oxides. To do this, we designed a study to investigate a range of local and averaged electrochemical, structural, vibrational, gravimetric, and mechanical behaviors of an electrodeposited birnessite film. The following chapter was conducted in collaboration with Nina

Balke and Wan-Yu Tsai at the Center for Nanophase Materials at Oak Ridge National Lab for operando atomic force microscopy. This manuscript is in preparation for publication.

4.1 Abstract

The origin of capacitive charge storage in transition metal oxides like birnessite has been of interest and debate since the first demonstration of capacitance in amorphous birnessite in

1999.80 Particular topics of debate are whether this behavior is faradaic (pseudocapacitive) or non- faradaic (EDL formation), and if it is faradaic, whether the response is due to surface or interlayer redox. In this study, we used ex situ X-ray diffraction (XRD), electrochemical quartz crystal microbalance (EQCM), in situ Raman spectroscopy, and operando atomic force microscope

(AFM) dilatometry in both K2SO4 and Li2SO4 to observe the behavior of a birnessite electrode during electrochemical cycling. These techniques were chosen because together they provide a holistic picture of the electronic, vibrational, structural, gravimetric, and mechanical response of birnessite. Additionally, this report is the first to show operando electrochemical AFM dilatometry of ion intercalation into a layered oxide material. The changes in interlayer spacing shown by XRD and Raman correspond to redox and mass change peaks from electrochemistry and EQCM, indicating that charge storage in birnessite is governed by interlayer rather than surface processes.

The film remains Raman-active throughout the cycling, showing that capacitive behavior occurs without a semiconductor-to-metallic phase transformation. Overall, these results show that interlayer processes involving the exchange of cations and water molecules dominate the capacitive behavior of birnessite, and that confinement within the ~ 7 Å hydrated interlayer spacing of birnessite interlayer blurs the distinction between EDL formation and pseudocapacitance.

4.2 Introduction

Electrochemical interfaces can be used for electrochemical energy storage (EES) via the formation of the electric double layer (EDL) and/or reversible surface and near-surface charge- transfer reactions, termed pseudocapacitance.39 Pseudocapacitance was first conceptualized in the

1940s to explain the existence of reversible charge transfer reactions not associated with the formation of the electrical double layer (EDL).226 The first of consideration of pseudocapacitance for energy storage materials occurred in 1971, with the discovery of the fast, reversible, and

40 capacitive-appearing charge storage behavior of RuO2 by Trasatti et al.. Pseudocapacitive EES devices combine the power densities of electrochemical capacitors with energy densities approaching those of insertion-type batteries.204,227

However, after 40 years of research there is still significant debate over the mechanisms which give rise to pseudocapacitance.41,116,228 At the core of this debate is the question: how can transition metal oxides store high amounts of charge without exhibiting obvious faradaic redox peaks? Pseudocapacitive behavior can be both intrinsic, as in hydrous RuO2, IrO2,

40,179,208,229 42,205 WO3·nH2O, or extrinsic, as in nanostructured LiCoO2 or V2O5.

Enter manganese, the 10th most abundant element in the earth’s crust, which crystallizes into over 30 oxide and hydroxide structures.13 Many of these structures exhibit capacitive behavior, and manganese oxides have subsequently been some of the most widely studied transition metal

40,179,208,229 oxides in aqueous electrolytes. Unlike many hydrous transition metal oxides, MnO2 is light, abundant, redox active in neutral-pH aqueous electrolytes, and does not exhibit a semiconductor-to-metallic transformation upon ion insertion. Lee and Goodenough documented the first observation of capacitive behavior in MnO2 in their 1999 paper, which describes highly

80 reversible charge storage in amorphous MnO2 in aqueous electrolytes. Many MnO2 structures are only capable of accommodating H+,130,190,222 and do not show appreciable Faradaic behavior in thick films.96 To understand the mechanisms underlying capacitive behavior, it is important to study materials with the potential for bulk ion intercalation. In this work, we use the birnessite

MnO2, (δ-MnO2, AxMnO2-yH2O, where ~0.1 < x < 0.7 and 0.3 < y <2) to investigate the

relationship between faradaic reactions and a relatively featureless CV. Birnessite has been widely studied because it is easily synthesized, similar to the layered oxides popular for secondary batteries, and can accommodate a variety of cations. Its flexible ~7 Å interlayer spacing, wherein alkali cations and water molecules electrostatically stabilize the MnO2 layers, renders birnessite a material of interest for EES applications as well as emerging technologies such as faradaic desalination and heavy-metal sorption.84,85,104–108 Practically, low conductivity is the main drawback of the MnO2 polymorphs. Here, this presents an opportunity to determine the origins of capacitive behavior in a hydrated layered material without a semiconductor-to-metallic transition.

Although MnO2 has been studied for > 20 years, there is still controversy over whether its charge storage is primarily due to EDL formation or faradaic redox. While elemental analysis shows significant alkali cation content after extended cycling, reports vary widely on whether the energy storage is due to surface behavior or interlayer incorporation of hydrated ions, ion intercalation and subsequent exchange, or opposing ion and water fluxes.120–122,230 Recently,

Costentin et al. have shown that according to electrochemical theory, rectangular CVs cannot be obtained from spread out or multiple redox peaks.116,231,232 In conjunction with Conway, they hypothesize that the large 1D or 2D diffusion channels for intercalated ions, which often contain structural water, act as an extended surface and attribute the quasi-rectangular “pseudocapacitive”

CV to EDL formation in the material interlayer.233,234 Typical surface-area normalized capacitance of manganese oxides, including birnessite, it is least one order of magnitude larger (> 100 µF cm-

2) than the 4-10 µF cm-2 of porous carbons.33,85,115 However, the structural water interferes with the gas absorption often used to measure surface area, so the potential contribution of hydrated interlayers to the surface are not necessarily accounted for.235

100

Alternatively, computational studies by Young et al. argue that in semiconducting oxides such as MnO2, all incorporated cations contribute to charge-storing electronic states throughout the band gap.81,98 This, along the variation of reaction potentials according to site energy, lead to a rectangular CV. The argument for faradaic redox processes is supported by several studies which showed the transfer of 0.2-0.6 e- per Mn within a ~ 1 V window using both in and ex situ X-ray

30,236–238 - absorption spectroscopy (XAS). While this is close to the capacitance of 0.18 e /atom capacitance Conway ascribes to planar metallic surfaces,22 ex situ XAS would not be able to measure a change in Mn oxidation state if the storage were purely capacitive.

These opposing perspectives highlight the debate surrounding the capacitive behavior of birnessite, also illustrated in Figure 1. While many studies have focused on one or two aspects of the response of birnessite to electrochemical cycling, there remains a lacking connection between localized and averaging techniques and theory calculations. To address this, we coupled ex situ

XRD, EQCM, in situ Raman spectroscopy, and operando AFM dilatometry to observe the structural, mass, and vibrational changes of the electrode during electrochemical cycling. These techniques were chosen because together they provide a holistic picture of the electronic, vibrational, structural, gravimetric, and mechanical response of birnessite to electrochemical signals. XRD allows us to see any changes in the interlayer spacing upon electrochemistry, giving insight into the structural/mechanical response. EQCM shows us the gravimetric response of the electrode, allowing us to determine if changes in the electrochemical signal or material structure are due to species leaving or entering the electrode. Raman spectroscopy indicates which bonds are most affected by the electrochemical behavior. It has been widely used to study birnessite, so it also allows us to correlate our results to the literature.77,96,121 Finally, AFM dilatometry shows the holistic electro-chemo-mechanical response of the electrode. 208,239 These techniques include

101

some which have been used for clearly faradaic reactions (XRD, EQCM, Raman), purely non- faradaic capacitive carbons (EQCM, AFM dilatometry), and pseudocapacitive systems (all). In addition, this is the first study using operando electrochemical AFM dilatometry on a layered oxide material which experiences ion insertion into the interlayer.

This paper uses a multi-modal experimental and theoretical study to determine which mechanisms give rise to the apparent pseudocapacitive behavior of birnessite MnO2 (δ-

K0.1MnO2·0.1H2O). By comparing the average (electrochemical, XRD, EQCM) to the local

(Raman, AFM dilatometry) electrode response, we show that the capacitive behavior of birnessite

MnO2 is due to interlayer ion insertion processes in both Li2SO4 and K2SO4. We show that capacitive behavior occurs in materials without the semiconductor-to-metallic transition. Lastly, this work indicates that confinement within a hydrated interlayer blurs the distinction between

EDL formation and pseudocapacitance.

Figure 1. Schematic of the proposed energy storage mechanism of A) the nanostructured birnessite, showing B) surface or C) interlayer processes.

102

4.3 Methods

4.3.1 Electrodeposition of Birnessite

Thin films of birnessite were synthesized via a cathodic electrodeposition method.240 The electrodeposition solution consisted of 50 mM KCl (source) and 2 mM KMnO4 (source) aqueous solution in a glass beaker cell. Films were deposited onto different gold-coated working electrodes depending on the subsequent analytical technique. Films for EQCM were deposited onto gold- plated 1” diameter AT cut quartz crystal sensors with a fundamental frequency of 5 MHz (Phillip

Technologies) and a working electrode area of 1.419 cm2. Films for XRD and AFM were deposited onto a 1 cm2 area of Au-coated glass slides with a 15 nm Cr adhesion layer. Films for in situ Raman spectroscopy were deposited onto ceramic screen-printed electrodes (SPEs, Pine Instruments), with a gold electrode active area of 3.14 mm2. All working electrodes were cleaned by sonication in acetone and ethanol prior to electrodeposition. Ag/AgCl in KCl served as the reference electrode

(Pine Instruments) and Pt wire as the counter electrode (99.997%, Alfa Aesar). Electrodeposition was performed by applying 0 V vs. Ag/AgCl until |0.4-0.5| C cm-2 using a Biologic MPG-2 potentiostat. Electrodes for XRD were held until 1 C cm-2 in order to obtain thicker films. Films for in situ Raman were deposited using a WaveNow potentiostat (Pine Instruments) compatible with the SPEs. A sample electrodeposition curve on an EQCM sample is shown in Figure 2. After electrodeposition, all electrodes were rinsed and dried at 60 °C in air overnight. Each electrodeposition solution was only used the day it was made for at most two electrodes due to the effect of spontaneous precipitation of δ-MnO2 over time on film morphology.

103

Figure 2. A typical electrodeposition curve from the EQCM, showing the chronoamperometic curve (black) and linear mass change (blue).

4.3.2 Physical Characterization

The morphology of the as-deposited film was observed using scanning electron microscopy

(SEM, FEI Verios 460L). X-ray diffraction (XRD) was performed using a Bragg-Brentano geometry and Cu-Kα radiation on a PANalytical Empyrean. Ex situ XRD was collected every 0.1

V from 0 – 0.85 V by cycling the birnessite electrode to the desired potential via linear sweep voltammetry (LSV) at 10 mV s-1. Peak fitting was done in Origin software using the pseudo-Voigt2 function, according to the procedure in Appendix C.

4.3.3 Electrochemistry

Electrochemical characterization was conducted in three-electrode cells with either a 0.5

M K2SO4 (Fisher Scientific) or Li2SO4 (Sigma Aldrich) electrolyte. The electrochemical cells consisted of electrodeposited birnessite working electrodes, Ag/AgCl reference electrodes, and Pt

104

counter electrodes as noted above. Electrochemical cells for EQCM, in situ Raman, and operando

AFM are described in the respective sections. Unless otherwise noted, all potentials in this work were measured vs. Ag/AgCl.

4.3.4 In situ Raman Spectroscopy

In situ Raman spectroscopy was conducted using a Witec Alpha 300 Confocal Raman

Microscope with a 532 nm Nd: YAG laser, an 1800 grooves/cm grating (spectral resolution ~1 cm-1), and 63x Zeiss water dipping objective lens. The laser wavelength was calibrated to the main peak in Si at 520 cm-1. Spectra shown here are the result of 5 20-second long accumulations.

During the electrochemical cycling, only 1-3 mL of electrolyte was used, just enough to fully over the working area of the SPE and allow full immersion of the objective tip. The electrode was cycled a few times at 10 mV s-1 between 0 – 0.8 V vs. the Ag/AgCl reference built into the SPE before prior to spectra collection. We collected spectra every 0.1 V between 0 and 0.8 V. The electrode was cycled to the desired potential at 10 mV s-1 using LSV and remained under constant applied potential during spectra accumulation. Origin software was used to subtract the background and fit the spectra using Lorentzian peaks.

4.3.5 Operando Atomic Force Microscopy (AFM) Dilatometry

AFM and operando AFM dilatometry measurements were conducted with a MFP-3D

AFM and an in situ electrochemical cell (both from Asylum Research, USA) using BudgetSensors

AFM tips (ElectriMulti75-G) with a spring constant of 3 N/m. Topography scans in air and in the electrolyte were conducted using the AC tapping mode. The in situ electrochemical cell contained the electrodeposited birnessite thin film, a leakless Ag/AgCl reference electrode (Asylum

105

Research, USA), a glassy carbon counter electrode, and was flooded with electrolyte. Electrodes were cut into 0.8 x 0.8 cm squares to fit into the cell. Silver paint (Asylum Research, USA) was used to electronically connect the top of the electrode to a conductive puck (Asylum Research,

USA) to complete the electrochemical circuit. Care was taken to ensure that the paint was not accessible by the electrolyte. After the paint dried, we assembled the electrochemical cell, checking the electronic connectivity at each step with a multimeter.

To pick points for single-point AFM dilatometry, we first conducted a large (~70x70 μm) scan to observe the large-scale morphology. Dilatometry was performed near the center of birnessite islands to avoid edge effects. The measurements were conducted by initiating a force- distance curve, which triggered the SP-300 potentiostat (Bio-Logic, USA) to run cyclic voltammetry (10 – 200 mV s-1) during the contact part of the force-distance curve. At rates of 50 mV/s and greater, we collected 7 CVs per rate. At the slower rates (10, 20 mV/s) we were only able to collect 1-2 cycles at a time. These experiments were limited by the fact that the tip readily drifted out of contact with the electrode at sweep rates below 50 mV/s. Datasets at slow rates are only shown here if the pull-off curve indicated that the tip remained in contact with the electrode throughout electrochemical cycling.The EC-Lab software recorded the time, working electrode potential, current, and the deflection of the AFM tip in volts. To convert the AFM deflection signal to distance, we took the slope of the linear portion of the retraction in the force-distance curve. We found that this value varied widely (from 56 to 105 nm V-1) as we changed samples and tips, but we used the clearest curves we could get. The resulting dilatometry data was analyzed using a

Matlab program (Appendix B) that applied a Savitzky-Golay filter to smooth the raw data and obtain the derivative of the deformation, similar to the procedure described by Wang et al..208

106

4.3.6 Electrochemical Quartz Crystal Microbalance (EQCM) Measurements

EQCM measurements were conducted using a QCM200 quartz crystal microbalance digital controller and QCM25 5 MHz crystal oscillator (Stanford Research Systems, Inc.). The mass of the deposited film was obtained from the resonant frequency of the dried crystal after

2 -1 electrodeposition using the Sauerbrey equation and the Cf for air, 56.6 Hz cm μg . After assembling the electrochemical cell for EQCM, it was allowed to thermally equilibrate for a minimum of 30 minutes prior to data acquisition. Cyclic voltammetry was conducted between 0 and 0.85 V at sweep rates from 200 – 5 mV s-1 using a Biologic MPG-2 potentiostat. EC-Lab software recorded the time, working electrode potential, current, crystal frequency, and crystal resistance during cycling. The tests were conducted using a 200 Hz V-1 conversion factor for the output signal on the QCM controller. 10 cycles were conducted at each sweep rate. The resulting data was analyzed using a combination of Matlab codes (Appendix B) and linear fitting in Origin.

4.3.7 EQCM Calibration

Although EQCM can be reliably used in liquid solutions,241 the viscous loading on one side of the crystal requires re-calibration of the conversion factor for the Sauerbrey equation:

∆푓 = −퐶푓∆푚

2 In air, Cf=56.6 Hz cm /μg. The mass change in aqueous electrolytes was calibrated according to protocol described in the SRS QCM200 manual and by Gabrielli et al.241,242 Silver was deposited and stripped from an aqueous solution of 0.05 M AgNO3 (Alfa Aesar) in 0.5 M HNO3 (Fisher) onto a new crystal at 100, 200, 300, and 400 μA/cm2, normalized to the overlapping area between the electrode on the back of the crystal and the active electrode on the front of the crystal. The

107

linear changes in frequency are shown in Figure 3A, below. We then used the following equation to calculate the equivalent Cf in Hz/g for each current density:

−퐹 × 푛 × ∆푓 퐶푓 = 푀푊퐴푔 × ∆푄

Where: F = 96485 C/mol e- n = # of electrons transferred (mol e-/mol Ag or other depositing species)

Δf = frequency change measured during deposition in Hz

MWAg = molecular mass of silver

ΔQ = charge passed during deposition in C

Plotting Cf vs. -log(i) (i = current density) gives Figure 3B. Here each Cf is clearly similar.

To obtain the experimental Cf of 24.42 ng/Hz we inverted the average of these values. All EQCM frequency change data was converted to mass before background subtraction.

Figure 3. Data from the EQCM calibration in 0.5 M HNO3 and 50 mM AgNO3. A) The frequency change during Ag deposition, showing a simple linear process. B) Calculated values of Cf at each current density, which were then averaged to obtain the experimental Cf.

108

4.3.8 Applicability of EQCM to Thin Films

In air, the change in frequency of the crystal used for EQCM was 4996892 – 4989701 =

7191 Hz, or 0.14% of the unloaded crystal’s resonance frequency. This means that the Sauerbrey equation can be used to calculate the mass of the deposit,241 which gives us 180.3 μg (127 μg/cm2).

With a total charge passed during electrodeposition of 0.562 C, and assuming a 3 e- reaction to

7+ 4+ 26 reduce Mn to Mn , the molar mass of the electrodeposited film is 92.8 g/mol. Plain MnO2 would be 86.9 g/mol, leaving ~5.9 g/mol unaccounted for. This leads to a maximum of 0.15 mol

+ + K with no interlayer water, or 0.33 mol H2O with no interlayer K . Since we expect both species to exist in the as-synthesized material, we propose the following composition: K0.1MnO2·0.1H2O.

When immersed in liquid, the unloaded crystal experiences a frequency drop of 640 Hz.

Once birnessite is deposited, the film drops by 1047 Hz. Relative to the theoretical drop of 715 Hz for a polished crystal going from vacuum to liquid,241 this is a reasonable change in frequency. We therefore confirm that this film is compatible with liquid-phase EQCM measurements.

4.4 Results and Discussion

Figure 4 shows the structure and morphology of the as-electrodeposited birnessite.

Birnessite is typically represented by a simplified version of the structure as in Figure 4A that show slabs of edge-sharing MnO6 octahedra, separated by a complex interlayer consisting of a single layer of water and cations in two similar but distinct sites in a periodic, wave-like array.104

Mn exists in both Mn4+ and Mn3+ states to balance the interlayer cation charge,243 and defects such as Mn vacancies are present.110 Figure 4B shows the XRD pattern, where the (001) reflection at

~12 °2θ corresponds to the interlayer spacing of 7.08 Å, consistent with a single layer of water.84,240

The Raman spectrum in Figure 4C shows the three primary peaks of birnessite, although defects

109

244 and local disorder can lead to variations in Raman peak position and relative intensity. The ν1

-1 peak at ~ 635-655 cm represents the octahedral Mn-O bond stretching and the ν2 peak at ~580

-1 121,244 -1 cm represents the basal plane Mn-O bond stretching. The ν3 doublet at ~500 cm is also indicative of the birnessite structure.77,244 SEM and AFM characterization in Figure 4D show that the electrodeposited films consist of “islands” 10-50 μm in diameter, with an average film thickness of 1.47 ± 0.78 μm (Fig. 5). These islands vary in density depending on the location on the current collector relative to the electrical connection, and the “age” of the deposition solution.

When first taken out of the deposition solution and rinsed, all samples had a dark red color with some slight rainbowing, indicating their relatively thin thickness. After drying, samples deposited from a fresh solution retained some of the red coloring, while samples from a previously-used solution (even if it was just once) dried into a brown color. The amount of color change after drying corresponds to the island size—a reddish color indicates a more uniform film with few islands, while a brown color indicates larger islands. At higher magnifications (Figure 4E), all samples consisted of nanosheet-like flakes oriented mostly perpendicular to the substrate. This is a common morphology for birnessite obtained via room-temperature synthesis or restacking exfoliated

15,31,110,240,245 nanosheets. AFM topography scans in 0.5 M K2SO4 (Figure 4F) show that the island morphology is maintained upon immersion into an electrolyte.

110

Figure 4. Structure and morphology of electrodeposited birnessite thin films. A) Model of the birnessite crystal structure, showing interlayer K+ (purple) and water (grey) species. B) XRD pattern showing the interlayer spacing peaks; reference peaks are from PDF 00-042-1317. C)

Raman spectrum showing the basal plane (ν2) and out-of-plane (ν1) Mn – O bond stretching modes.

D) SEM image of large “islands” that form at the bottom of an electrode furthest away from electrical contact. E) Higher magnification SEM image of birnessite nanosheets showing the tissue-like morphology. F) AFM liquid AC tapping mode image in 0.5 M K2SO4 electrolyte showing the “island” morphology is preserved upon immersion into a liquid. The white squares show the locations of the two points measured in Section 4.3.2.

111

Figure 5. Film thickness calculated from A-C) SEM cross-sections and D) corroborated with AFM cross-sections. The SEM gives an average film thickness of 1.47 ±0.78 μm, and the AFM height trace across one of the islands shows an overall film thickness of 1-2 μm (1.4 μm in the spot shown), with raised edges and flatter island centers.

4.4.1 Global Techniques: Electrochemistry, Ex situ XRD, and EQCM

Electrochemical characterization via cyclic voltammetry of the electrodeposited birnessite films (Fig. 6) shows the typical quasi-rectangular behavior birnessite in neutral pH electrolytes. In both K2SO4 and Li2SO4 the CVs show a large capacitive current contribution, broad reversible peaks between 0.3 and 0.7 V, and nearly ideal switching in current polarity at the vertex potentials.

The capacitance of the film is 158 F g-1 at 5 mV s-1, and 71 % of the charge storage is maintained at 200 mV s-1. The capacity (37 mAh g-1) corresponds to the storage of 0.13 e- per Mn.

112

Figure 6. Electrochemical performance of birnessite MnO2 in 0.5 M K2SO4 (black) and Li2SO4

(green, dashed). A) CV at 10 mV s-1 showing a quasi-rectangular shape. B) Capacitance (and capacity) as a function of scan rate, showing 71% capacity retention from 5 to 200 mV s-1 and that at this film thickness, the behavior of birnessite is the same in both electrolytes.

Having established the structure, morphology, and electrochemical behavior of the electrodeposited birnessite, we now address the mechanisms which give rise to its capacitive behavior. We will first discuss the techniques which average signal over the entire electrode (ex situ XRD, EQCM), followed by local techniques (in situ Raman, operando AFM). We conducted ex situ XRD at 100 mV intervals to observe the overall structural changes upon electrochemical cycling. Figure 7 shows the full patterns and the shift of the (001) peak as a function of potential, with overall changes of 0.1 Å in K2SO4 and 0.17 Å in Li2SO4. This data shows that the interlayer expands upon oxidation, and contracts upon reduction. Several studies on birnessite have shown redox between Mn4+/Mn3+ within the 0 – 1 V window using in and ex situ X-ray absorption spectroscopy,236–238,246 and ex situ X-ray photoelectron spectroscopy96,218 This, and the fact that the changes in interlayer spacing coincide with the broad peaks observed in cyclic voltammetry

113

indicates that charge storage within this region primarily involves the interlayer. The extent of interlayer spacing change observed here is similar to previous reports that the interlayer spacing expands by 0.1 – 0.2 Å during oxidation.15,24,25,120,218 XRD peaks of lattice planes with a- and b- axis components are not visible in our data due to location of the Au substrate peak and the nanocrystalline nature of the sample. Previous operando diffraction studies show that the increase in interlayer spacing upon oxidation is accompanied by a decrease in the a and b lattice parameters, leading to an overall ~ 0.5% decrease in unit cell volume.24,25 The increase in interlayer spacing upon oxidation is generally considered to occur from increased electrostatic repulsion between

15,218,244 MnO2 layers due to decreased electrostatic shielding upon cation deintercalation, or the incorporation of water to offset the repulsion.77

We conducted EQCM to measure mass change and determine the species involved in the charge storage mechanism. Figure 8 shows a relatively linear mass loss with oxidation and reversible increase with reduction over the entire potential range, consistent with prior reports for birnessite in aqueous electrolytes.26–31 The continuous mass loss upon oxidation indicates that cations are the dominant species involved in the charge storage, as anion involvement would result in mass gain upon oxidation. Additionally, the slight hysteresis which appears around the 0.3 – 0.7

V window shows there may be kinetic limitations from mass transfer into the interlayer. The dominant species involved in charge storage is determined by a material’s point of zero charge

(PZC), or the potential where the negative and positive species have equal concentrations at the material surface. In transition metal compounds typically used for secondary EES, this is determined by pH. If the electrolyte pH < pHPZC, the surface will be positively charged, and anions

124,125 will dominate charge storage. If the electrolyte pH> pHPZC, the surface will be negatively charged, and cations will dominate. The pHPZC of birnessite is below pH 4, so in the neutral pH

114

108,124–126 K2SO4 and Li2SO4, cations are expected to dominate the charge storage mechanism. The

PZC of carbons is not governed as strongly by pH, allowing capacitors to be polarized to either side of their PZC and experience non-faradaic contributions from both anions and cations.

Figure 7. Ex situ XRD of birnessite. A) The full patterns taken on the electrode cycled in K2SO4 show no shift of the Au substrate peak, while B) the normalized (001) peak shows interlayer expansion. The same is observed in Li2SO4, where C) shows the full patterns and D) shows the normalized (001) peak.

115

Figure 8. Mass changes vs. potential of birnessite MnO2 in A) K2SO4 and B) Li2SO4. The mass change in K2SO4 is only ~twice that of the change in Li2SO4, indicating that bare ions as not the only involved species—if they were, the mass changes would be 9.6 μg in K2SO4 (atomic mass of

K = 39 g/mol) and 1.7 μg in Li2SO4. This, in addition to the MCR values, indicate that multiple species are involved in the charge storage. However, the relatively constant mass change in both electrolytes does indicate that even if there are multiple mechanisms involved, they do not differ much from each other.

Our mass-charge ratio (MCR) calculations (Table 1), which show the effective molar mass of the species passed per charge, give positive values, confirming the cation-dominated mechanism. Figure 9 shows the average of 10 cycles at 10 mV s-1 that the MCR lines were fit to.

116

Table I. Mass-charge ratios of birnessite in K2SO4 and Li2SO4 at 10 mV/s

K2SO4 Li2SO4 Potential MCR Potential MCR e-/mol MnO e-/mol MnO Range (V) (g/mol e-) 2 Range (V) (g/mol e-) 2 0 – 0.65 V 30.6 ± 0.1 0.09 0 – 0.55 14.4 ± 0.05 0.08

0.63 – 0.85 18.9 ± 0.3 0.05 0.55 – 0.85 8.77 ± 0.03 0.05

0.85 – 0.52 22.4 ± 0.27 0.03

0.85 – 0 26.4 ± 0.02 0.14 0.51 – 0.21 12.3 ± 0.07 0.05

0.21 – 0 6.66 ± 0.18 0.05

Figure 9. Plots of Potential and Mass vs. Charge for A) K2SO4 and B) Li2SO4. There are 3 distinct sections in K2SO4, and 5 (two anodic, and 3 cathodic) in Li2SO4. These indicate that there may be multiple processes involved in the charge storage mechanism of birnessite MnO2.

If only the bare cations were involved, we would expect an MCR of 39.1 g/mol e- for K+, which is not obtained over any potential range. Instead, there are two clear regions in the anodic cycle, with an MCR of ~30 g/mol e- between 0 and 0.65 V, and an MCR of 19 g/mol e- between

117

0.63 and 0.85 V. Based on these values, we propose the following mechanisms for each potential region during the anodic sweep:

0 to 0.65 V:

− + 퐾0.1푀푛푂2 ∙ 0.1퐻2푂 − 0.09⁡푒 − 0.09퐾 + 0.04퐻2푂 → ⁡ 퐾0.01푀푛푂2 ∙ 0.14퐻2푂

0.63 to 0.85 V:

− + 퐾0.01푀푛푂2 ∙ 0.14퐻2푂 − 0.05⁡푒 − 0.05퐻3푂 → ⁡ 퐾0.01푀푛푂2(푂푂퐻)0.01 ∙ 0.06퐻2푂

There is only one MCR in the cathodic cycle (26 g/mol e-), which suggests the kinetics of ion insertion may be slower than those of ion extraction, and leads to the following mechanism:

− + + 퐾0.01푀푛푂2(푂푂퐻)0.01 ∙ 0.06퐻2푂 + 0.14⁡푒 + 0.09퐾 + 0.04퐻 → ⁡ 퐾0.1푀푛푂2 ∙ 0.1퐻2푂

+ The first anodic step (0 to 0.65 V) is similar to that proposed by Arias et al., where Na and H2O always moved in opposing directions.114 We note that while these are possible reactions, it is conceivable for many other reactions and ratios of species would also fit the data. For example,

+ + + - parallel fluxes of H3O and K or opposing fluxes of K and OH are also possible.

The EQCM behavior is more complex in 0.5 M Li2SO4, with two MCR regions in the anodic cycle, and three in the cathodic cycle. The values again indicate that multiple species are involved in most of the charge storage mechanisms. While desolvated Li+ transport has been reported in

29 MnO2 systems, here only the final MCR value from the cathodic sweep in Li2SO4, 6.66 ± 0.18 g/mol e-, is similar to the expected value for a bare ion. Additionally, all the MCR values are lower than expected for typical hydrated Li+,28,114 suggesting that two charged species may be participating in the reactions. Opposite to behavior observed in K2SO4, the first part of the anodic sweep (from 0 – 0.55 V) represents the average of the first two sections of the cathodic sweep

(from 0.85 – 0.21 V). This indicates that Li+ removal is more difficult than inserting it, likely due

118

+ to the strong interactions between Li and birnessite. The opposite trend occurs in K2SO4, which is to be expected due to the lower point charge density of K+.

The MCR calculations do not provide a definitive answer to which cationic species are involved in the charge storage. Most studies of birnessite in neutral-pH aqueous electrolytes agree that the alkali cation in the electrolyte is the primary charge-carrying species.26–31,114 Commonly, water molecules or protons are used to explain discrepancies from expected MCRs. The constant mass change over the entire potential range is interesting because it suggests that the same species contribute to both surface and interlayer storage. In particular, we do not see sudden mass changes without a corresponding change in charge that would indicate ion-exchange30,122 or water movement without coordinated cation movement.15,31,77,121,247

4.4.2 Local Techniques: In Situ Raman Spectroscopy and Operando AFM

To observe the effect of electrochemical cycling on the vibrational structure of the birnessite electrode and obtain in situ data to correlate interlayer spacing with the ex situ XRD, we conducted in situ Raman spectroscopy. Figure 10 shows the normalized cumulative fit curve of

-1 spectra taken every 100 mV. The primary feature here is the reversible ~ 14 cm shift of the ν1 peak upon oxidation to 0.8 V and reduction to 0 V. Similar trends occur in Li2SO4.

119

Figure 10. Cumulative fit curves of the in situ Raman spectra of birnessite during aqueous electrochemistry in A) K2SO4 and B) Li2SO4. The spectra show an increase in Raman shift of the

ν1 peak, and a relatively stable ν2 peak.

Both the ν1 and ν2 peaks are sensitive to the interlayer environment, but they typically exhibit opposite behaviors upon electrochemical oxidation and reduction. The ν1 peak center increases in wavenumber and intensity with oxidation, while the wavenumber of the ν2 band often decreases with oxidation.77,121,244,247 These shifts are believed to represent weaker interlayer

4+ interactions, an increase in the amount of Mn , and an un-wrinkling/stiffening of the MnO2 layers as the Mn oxidation and interlayer cation deintercalation reduces local distortions in the oxide

77,121,244 layers. In addition, the change in relative intensity ratios as ν1 intensifies and ν2 loses intensity is attributed to the increasing lattice spacing and overall ordering of the structure upon oxidation.31,77 The in situ Raman spectroscopy changes strongly point to the presence of faradaic reactions, since we do not expect EDL formation to affect the bonding environment of MnO2.

120

AFM dilatometry experiments were conducted in 0.5 M K2SO4. These measurements allow us to detect the electrochemically-induced deformation changes of the electrode in real time and in a particular location on the electrode surface. The AFM topography image in Figure 1F shows the morphology and chosen points for dilatometry in K2SO4. These points were chosen because they are in the center of the islands, where the flakes are more likely to be semi-perpendicular to the electrolyte surface as shown in Figure 1E. It is important to note that the measured deformation shows the response of the birnessite unit cell, and is not clearly defined with respect to the birnessite crystal structure due to the random orientation and thickness of the electrodeposited

-1 films. Figure 11 shows averaged AFM dilatometry at 10 and 50 mV s in 0.5 M K2SO4 and at 50

-1 mV s in Li2SO4. Both electrodes contracted during oxidation and expanded during reduction, by

10 ± 5 nm in Li2SO4 and 17.3 ± 2.2 nm in K2SO4. Unfortunately, these rates were slow for the

AFM technique, and the tip readily drifted out of contact with the electrode surface. Because of this, we were unable to conduct AFM dilatometry at 10 mV/s in Li2SO4. Increasing the set point voltage (the force with which the tip pressed on the sample) altered the signature of the material, so we had to work with noisy data at slow rates. The deformations curves in K2SO4 at 10 and 50 mV/s have the same beginning and end point, showing that the material deformation remained the same. Also shown is the lack of deformation of the gold substrate, as expected for a non-porous electrode not undergoing charge storage. However, the deformation became more polarized, as the anodic deformation (solid line) at 50 mV/s is shifted about 0.2 V to the right. Due to the limitations in K+ insertion discussed above, the cathodic deformation (dashed line) is less polarized, showing that the material has more time to adjust as the K+ slowly inserts into the interlayer. The hysteresis

208 exhibited in both electrolytes is higher than that observed in WO3-2H2O, which may indicate slower responses due to the exchange of water and cations rather than simple H+ incorporation.

121

-1 The deformation of birnessite in Li2SO4 at 50 mV s in Figure 11B shows significant hysteresis and lower deformation than the material in K2SO4. This may be a result of larger interlayer expansion countering the overall volume change. The gold background at 50 mV/s

(“Au”) was taken on a fresh electrode and shows essentially no deformation. In Figure 11B, the

Au signal was measured in a visibly shiny area of an electrode where the birnessite had delaminated. Therefore, we hypothesize that the greater response of the Au signal in Figure 11B may be due to residual birnessite. Notably, the Au substrate (dashed line) in Li2SO4 indicates that when surface double-layer behavior dominates, expansion upon oxidation is expected. The deformation behavior matches that of capacitive carbons when polarized to the left of the PZC (the cation-dominant region), supporting our hypothesis of a cation-dominated mechanism.208,248–252

For a film 1.5 ± 0.2 μm thick, the change of 17.6 ± 2.5 nm in K2SO4 corresponds to a ~ 1.2% change in the film overall, similar to the 1.4% change in the c-axis measured by the XRD.

However, the ex situ XRD in Figure 7 shows that the interlayer (c-axis) spacing expands upon ion extraction. Because this is the only dimension of the electrode material capable of changing due to electrostatic or steric forces, the overall electrode contraction may be due to a change in bond lengths within the MnO2 layers from a faradic reaction, or a change in bond angle.

122

Figure 11. Deformation of birnessite in A) K2SO4 and B) Li2SO4. The deformation curves of birnessite at 10 and 50 mV/s in K2SO4 almost entirely overlap, indicating the same charge storage mechanisms at both rates. The noisy deformation signal in Li2SO4 is due to poor contact of the

AFM tip with the electrode during cycling.

The strength of this study is its combination of the local and averaging techniques which detect the structural, mechanical, and gravimetric mechanisms coupled with electrochemistry of birnessite. all the techniques. Figure 12 shows the summary data from each technique described above,. Overall, it shows that interlayer ion insertion is the driving force behind the pseudocapacitive behavior of birnessite. Figure 12A-B show changes in interlayer spacing as a function of potential in K2SO4 and Li2SO4, respectively. In K2SO4, the initial interlayer spacing of

7.1 Å at 0 V vs. Ag/AgCl increases by 1.4% upon oxidation to 7.2 Å at 0.85 V, and reversibly decreases to 7.08 Å upon reduction to 0 V. Most of the interlayer spacing change is potential- dependent, occurring between ~0.3 - 0.6 V during oxidation, and ~0.5 – 0.2 V during reduction.

In Li2SO4, the interlayer spacing increases by 2.4% from 7.03 Å at 0 V to 7.2 Å at 0.85 V, and back to 7.04 Å at 0 V. Here the interlayer spacing appears to change much more linearly with

123

potential, unlike in K2SO4. The limited potential range where birnessite in K2SO4 exhibits interlayer change suggests that charge stored at the extreme potentials in a K2SO4 electrolyte does not involve the interlayer. On the other hand, the interlayer spacing changes more linearly in

Li2SO4, indicating the interlayer may be active throughout this potential window.

While XRD shows the average change in interlayer spacing, it does not confirm what leads to that change. Another way of examining this is comparing the mass and current changes. To do this, we plotted the gravimetric CVs (‘gCV’, also termed ‘massogram’), or potential vs. -δm/δt, the negative of the time derivative of the mass. Because the current is the time derivative of the charge passed, if the gCV and CV curves line up, it indicates the reaction follows Faraday’s Law— the peaks in the CV are directly correlated to potential-dependent mass changes.27,253 Figure 12C shows that for a film ~1.5 um thick in an 0.5 M K2SO4 electrolyte, the gCV has a broad peak from

0.4 – 0.7 V (anodic cycle) and 0.6 – 0.3 V (cathodic cycle), indicating that the peak is due to the mass change. Compared with the XRD, this shows that the mass change likely leads to the change in interlayer spacing. Therefore we determine that the CV peak in the 0.5 M K2SO4 electrolyte is due to (de)insertion of interlayer species. Figure 12D shows the same is true in Li2SO4.

The ν1 peak shift in Figure 12E-F mirrors the interlayer change spacing measured with

XRD. As discussed above, this corresponds to interlayer expansion and contraction. In K2SO4 the most change occurs from 0.3-0.8 V of the anodic cycle, and the change does not reverse until after

0.6 V during the cathodic cycle. In Li2SO4, the ν1 peak shifts with potential, but the data is too noisy to determine whether this change occurs within a confined potential range. The ν2 peak barely shifts in either electrolyte, unlike other reports of an 8-15 cm-1 shift.31,77,121,247

Finally, we observe the overall mechanical response of the electrode by taking the negative time derivative of the deformation data. As described by Wang et al.,208 this generates a mechanical

124

CV (mCV) that shows the relationship between charge passed and material deformation—aligned features in the CVs and mCVs indicate that the charge-storage events lead to corresponding

-1 mechanical changes in the electrode. The mCVs of birnessite at 50 mV s in K2SO4 and Li2SO4 are shown in Figure 12G-H. Two sets of peaks are visible in K2SO4, indicating that multiple ion insertion sites may be present. The peak ~0.6 V corresponds to the interlayer process observed with XRD, EQCM, Raman, and electrochemistry. The peak near the cathodic potential, which was not seen in other techniques, highlights the ability of AFM dilatometry to detect local changes that are averaged out in global techniques like EQCM and electrochemistry. In the Li2SO4 electrolyte at 50 mV/s, the biggest change in the mCV occurs near the cathodic potential, indicating that the high current response in that region is due to a higher ion flux. The detection of deformation changes before electrochemical detection of Faradaic charge transfer shows that global electrode response is somewhat diffusion-limited. The AFM dilatometry can detect changes more quickly than the electrochemistry because the low conductivity of birnessite limits the e- transfer. The decrease in both the gCV and the mCV after the redox peak show that the increased current observed is due to the parasitic oxygen evolution reaction, rather than a material response.

While the interlayer is clearly involved, none of these techniques definitively assign either faradaic or non-faradaic character to the ion insertion processes. We are collaborating with theory groups to investigate the changes in electronic structure upon electrochemistry and determine the extent of interaction between interlayer cations and oxygens. However, it has been shown in activated carbons that ion insertion into pores < 1 nm leads to significant increases in capacitance, and the proposed in-pore environment appears quite similar to ion insertion typically associated with faradaic processes.254 Based on this observation, we propose confinement within a hydrated interlayer blurs the distinction between faradaic and non-faradaic ion insertion processes.

125

Figure 12. Multi-modal characterization of birnessite MnO2 in K2SO4 (left) and Li2SO4 (right), showing the results of each technique as a function of potential. A,B) Ex situ XRD shows reversible changes in interlayer spacing. C) gCV in 0.5 M K2SO4 at 10 mV/s shows that the current is directly related to mass changes, while in D) Li2SO4, the EQCM is more sensitive than the electrochemical signal. E,F) Shift of the Raman ν1 peak corroborates the interlayer spacing change shown finrom

XRD. G, H) CVs and mCVs at 50 mV/s from operando AFM dilatometry show that multiple processes occur during electrochemical cycling that combined lead to the CVs. 126

4.4.3 Rate-Dependence of AFM and EQCM Data

Having shown that birnessite stores charge via interlayer processes, we now consider the effect of sweep rate. Figure 13 shows the rate-dependent deformation (A, B) and mass change (C,

D) of birnessite. The deformation of birnessite exhibits slight decreases and corresponding increases in hysteresis with rate in K2SO4. A similar trend is observed in Li2SO4, where we attribute the apparent hysteresis at 50 mV/s to the tendency of the AFM tip to drift out of contact with the electrode. This was not a problem at 200 mV/s, so we attribute the observed hysteresis to actual hysteresis in sample deformation. The mass change is similar in both electrolytes.

Figure 13. Rate behavior of birnessite. Deformation from 50 – 200 mV/s in A) K2SO4 and B)

Li2SO4, Difficulty maintaining contact during AFM dilatometry led to increased hysteresis in the data at 50 mV/s in Li2SO4. The mass change from 20 – 200 mV/s in C) K2SO4 and D) Li2SO4. The films behave similarly in both electrolytes, with little visible hysteresis until 200 mV/s.

127

Figure 14 shows the change in MCR with sweep rate. In the K2SO4 the MCR increases with sweep rate, which may indicate that fewer water molecules are moving in opposition to the

+ inserting K . In Li2SO4, the decrease of the first voltage segments in both the cathodic and anodic sweep (0-0.55 V and 0.85-0.52, respectively) also suggests that less water is involved in the charge storage reactions. The increasing MCR at later points in the anodic and cathodic sweep rate show that these waters may move more slowly.

Figure 14. MCRs as a function of sweep rate in A) K2SO4, and C) Li2SO4. In K2SO4, MCRs slowly increase with sweep rate. If the species involved as the electrolyte cation and free waters, as we expect, in K2SO4 this may indicate that there is less opposing H2O flux with increasing sweep rates. In Li2SO4 the first segment during each potential sweep quickly decreases with sweep rate, while the later segments slowly increase. This suggests that fewer waters are also involved with increasing rate in Li2SO4. ‘a’ denotes anodic, and ‘c’ denotes cathodic.

Figure 15 shows the rate-dependent CVs, mCVs, and gCVs of birnessite MnO2 in both

Li2SO4 and K2SO4. There are two sets of peaks in the K2SO4 mCV (Fig. 15C), while the CV (Fig.

15B) and mCV (Fig. 15D) in Li2SO4 are have the same shape. This supports our earlier claim that

128

the AFM can detect processes not visible in global measurement techniques, and that there may be multiple processes occurring in the K2SO4 electrolyte. In Figure 15E the overall gCV and CVs in K2SO4 (Fig. 15E) shapes remain the same, showing increasing polarization with sweep rate.

However, in Li2SO4 (Fig. 15F) the gCV and CV peaks occur around the same potential at 20 mV/s, after which the gCV peak becomes progressively polarized, eventually shifting past the redox peaks. This may indicate the strong interaction between the Li+ ions and the birnessite electrode— as sweep rate is increased, a higher driving force is required to remove them from the electrode and re-insert them. The faster diffusion of K+ compared to Li+ and its lower electrostatic interactions with the electrode as the gCV behavior remains nearly the same from 20 – 200 mV/s with only slight polarization.

129

Figure 15. Electrochemomechanical and gravimetric behavior of birnessite as a function of rate.

The CVs from the operando AFM cell in A) K2SO4 and B) Li2SO4 show some polarization but

-1 maintain their shape from 50 to 200 mV s . The mCVs in C) K2SO4 show two clear sets of peaks, while in D) Li2SO4 the mechanical behavior mirrors the CV. Finally, CVs and gCVs in E) K2SO4 match, while in F) Li2SO4 the gCV peak is polarized beyond the CV peak at high rates.

130

The polarization at higher rates is to be expected, as the relatively low electronic conductivity of birnessite and the ~2D ion diffusion through the longer dimensions of the nanosheets delays interlayer ion insertion.255 Here we must also point out an important difference in the samples used: the films used for AFM dilatometry had a higher areal mass loading than those used for EQCM. This additional thickness may contribute to the triangular CV in the Li2SO4 electrolyte—it is likely that increased tortuosity in the film required more Li+ to desolvate to go into the interlayer. That is, the density of interlayer openings at the surface is lower, so the diffusion of Li+ through birnessite is more apparent with the higher mass loading. This CV shape is reminiscent of capacitive carbons which are size-selective for certain ions and require the ion to partially desolvate before inserting into the pore.254,256 In the EQCM sample, the higher surface : volume ratio of the thinner film gives rise to a CV without ion-selective behavior, maintaining clear interlayer peaks and capacitive behavior. The samples used for K+ exhibit this to a lesser extent, although it does appear that the peaks leading to interlayer behavior are shifted to higher potentials. This may be because the exchange of K+ with water occurs at higher rates than Li+, or that the large hydrated radius of Li+ slows its diffusion.

The differences in these two electrolytes highlights the importance of considering the interactions between the electrode, electrolyte, and electrolyte salt, when discussing electrochemical behavior. Here, the higher point charge density of the Li+ slowed it down, as the high interaction between the cation and its solvation shell meant that desolvation could not occur

+ at higher rates. In K2SO4, where the K interacts much more loosely with its solvation shell, the changes with rate were primarily less water exchanged. Overall, the interlayer water does appear to improve the structural integrity and rate capability of birnessite MnO2. However, if an opposing water flux is critical to the good pseudocapacitive performance of birnessite MnO2 in K2SO4, the

131

reduced water exchange with K+ may lead to reduced room for K+ in the interlayer and therefore reduced capacitance. These data do show that the charge-storage in birnessite is still due to interlayer mechanisms.

4.5 Conclusions

By conducting this multi-modal experimental study, we determine that the capacitive behavior of birnessite originates from interlayer processes where nanoconfinement within a hydrated interlayer blurs the distinction between EDL formation and pseudocapacitance. Using ex situ XRD, in situ Raman spectroscopy, EQCM, and operando AFM dilatometry, we observe both the local and global electrode response to electrochemical cycling. This combination of techniques shows that the material interlayer is clearly involved, and changes in the Mn-O bond lengths due to Faradaic charge transfer reactions are involved in the structural and mechanical changes of the electrode. While the interlayer expands during oxidation, the AFM dilatometry shows the electrode contracts, as expected upon cation deinsertion. The mass changes of the electrode confirm that cations are the dominant charge-storing species, and suggest that the exchange of cations and water from the interlayer enable the capacitive behavior of birnessite. Overall, this work shows that the complex mechanisms leading to capacitive behavior in birnessite MnO2 are primarly due to interlayer behavior, where the horizon between faradaic and non-faradaic processes becomes hazy due to the confinement within interlayer.

4.6 Acknowledgements

S.B. was supported by the National Science Foundation Graduate Research Fellowship

Program under Grant No. 571800. XRD and SEM studies were supported as part of the Fluid

Interface Reactions, Structures and Transport (FIRST) Center, an Energy Frontier Research Center

132

funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences.

This work was performed in part at the Analytical Instrumentation Facility (AIF) at North Carolina

State University, which is supported by the State of North Carolina and the National Science

Foundation (award number ECCS-1542015). The AIF is a member of the North Carolina

Research Triangle Nanotechnology Network (RTNN), a site in the National Nanotechnology

Coordinated Infrastructure (NNCI). Operando AFM was conducted at the Center for Nanophase

Materials Sciences, which is a DOE Office of Science User Facility.

133

CHAPTER 5

Summary and Outlook

My research focused on answering fundamental questions regarding the interlayer chemistry and aqueous electrochemistry of layered manganese-rich oxides, with the goal of providing the scientific basis for further development of EES materials and devices. This dissertation represents two approaches to understanding how the interlayer of manganese-rich oxides determines their structural and electrochemical behavior. The first approach, used for

Chapters 2 and 3, investigated the effect of the interlayer environment on the behavior of P2

NaxMO2 by varying the transition metal content. In non-aqueous Na ion electrolytes, this determines whether the material charges via a solid-solution mechanism or by undergoing many phase transformations, and can tune the capacity from 90-216 mAh/g.153,160–165 As mentioned in section 1.3.2, P2 oxides offer a potential new family of materials to meet the need for higher capacity aqueous Na ion battery cathodes. In Chapter 2, I investigated four manganese-rich P2 oxides with varying transition metal content to discover the effect of interlayer chemistry on their structural and electrochemical response to aqueous electrochemistry. This was the first study which connected the electrochemical performance of P2 oxides in aqueous electrolytes to their structural response. Although all materials had the same structure, I found that transition metal content determined the extent to which Na+ deintercalation led to spontaneous interlayer water uptake, expanding the interlayer spacing by 25%. In particular, the NaNMFe spontaneously formed a hydrated phase upon exposure to the electrolyte, whereas NaMCu had to be charged above ~1 V vs. Ag/AgCl for this phase transformation to occur. This can be attributed to the increased redox potential of the NaMCu material due to the presence of Cu2+.160,165,219 We used

STEM, XRD, and electrochemistry to investigate the behavior of these materials. In addition, we

134

observed that after water intercalation, the electrodes exhibited a more capacitive CV, although they eventually failed due to loss of electronic connectivity within the electrode. Through this work, we demonstrated that the water intercalation into P2 oxides can be tuned by the interlayer chemistry, and for the first time connected the transition metal content to electrochemical and structural behavior of P2 oxides in aqueous electrolytes. This is a valuable understanding when designing materials for use in aqueous electrolytes.

In Chapter 3, I developed a synthesis technique to take advantage of the capacitive behavior observed following electrochemical expansion and interlayer hydration of P2 oxides in aqueous electrolytes. First, I confirmed that the hydrated phase remained electrochemically active after water insertion using in situ synchrotron XRD. This showed that these micron-sized electrochemically active hydrated particles had potential for high rate and high volumetric capacity

EES, if their hydrated interlayer indeed supported faster ion diffusion. To circumvent the electrode failure observed in the previous chapter, I developed an electrochemical expansion process capable of hydrating ~0.5 g of P2 oxide particles. This facile process produces expanded particles, which

I subsequently assembled into slurry electrodes. Comparison of pristine P2 vs. expanded materials showed that pre-expanding the particles greatly improved electrode integrity. Preliminary comparisons with commercial activated carbon show that these expanded oxides have a higher volumetric capacitance at charge times greater than 40 seconds. This confirms that the expansion must enable significantly faster interlayer diffusion, as the surface area of the expanded particles is two orders of magnitude smaller than that of the activated carbon. Therefore, I showed that electrochemical expansion and interlayer hydration of large micron-scale particles is a viable alternative to nanostructuring for electrochemical capacitor materials. The process of electrochemical expansion is easily scaleable, and can be applied to a diverse range of materials.

135

The next steps for this work are to first, improve the repeatability of the synthesis by ensuring consistent electronic contact with all particles during expansion. Second, to further study these materials and determine the exact charge storage mechanisms. Third, to investigate the impact of electrode architecture: how does the electrochemical performance scale with electrode thickness?

Fourth, to apply this process to other materials to verify the versatility of our electrochemical expansion process. Taking these steps will greatly promote the development of large (micron- scale) hydrated particles for high rate EES.

As mentioned above, in this dissertation I approach understanding the effect of interlayer environment on the structural and electrochemical behavior of manganese-rich oxides two ways.

Chapters 2 and 3 represent the first approach: observing the effect of varying material composition and structure on the electrochemical performance. The second is to take a material with a known behavior and investigate the role of the interlayer. I used this approach in Chapter 4 to determine how the hydrated interlayer of manganese-rich oxides leads to their capacitive performance through a multimodal study on electrodeposited films of nanostructured birnessite. The primary questions surrounding birnessite include: is its capacitive behavior due to surface or interlayer processes; and if interlayer processes, are they due to EDL formation or faradaic behavior? To study this, I conducted one of the first holistic studies on birnessite, studying the structural, gravimetric, and mechanical responses to electrochemistry. I used in situ Raman spectroscopy and ex situ XRD to establish the interlayer behavior during electrochemistry. I coupled this with

EQCM to gain insight into the involved species, and operando AFM dilatometry to show the local mechanical response during electrochemistry. By comparing the average (electrochemical, XRD,

EQCM) to the local (Raman, AFM dilatometry) electrode response, I show that the capacitive behavior of birnessite is due to the exchange of cations and water molecules from the interlayer,

136

where the confined environment blurs the distinction between EDL and faradic processes. The capacitive behavior is likely due to the mitigated structural changes allowed by cation and water exchange, and the confined interlayer environment. Additionally, this work shows that capacitive behavior due to non-surface processes is possible in materials without the semiconductor-to- metallic transition. This is the first work to use operando AFM dilatometry to show the structural effect of ion intercalation into the interlayer of a layered transition metal oxide. By comparing the local and averaged electrode responses to aqueous electrochemistry, I discovered that as in porous carbons, the interlayer confinement blurs the distinction between faradaic and EDL processes, which leads to the pseudocapacitive electorchemical response. Moving forward, additional studies

I initiated on the effect of surface area : volume ratio on the charge storage processes of birnessite

(Appendix D) present a promising starting point to determine whether the rectangular CV is due to multiple processes or simply the interlayer flexibility. Additionally, studies on isotope effects and varying electrolyte concentrations are of interest to further determine the effect of interlayer and electrolyte water molecules on the charge storage mechanisms of birnessite.

Overall, my dissertation represents important discoveries on the effect of interlayer hydration on the aqueous electrochemical performance of manganese-based oxides. I showed that interlayer hydration improves the charge storage kinetics in micron-sized particles, presenting a new materials synthesis paradigm for electrochemical capacitor materials. I also connected the capacitive behavior of nanostructured birnessite to interlayer ion insertion processes, and made an important discovery that the confined interlayer environment blurs the distinction between EDL and faradaic processes. Moving forward, these understandings should be applied to investigate the effect of interlayer hydration and confinement on other materials systems to further develop a

137

fundamental understanding of the interactions between electrode materials and aqueous electrolytes, and enable the design of high performance aqueous EES devices.

138

REFERENCES

1. Boyd, S. & Augustyn, V. Transition metal oxides for aqueous sodium-ion electrochemical

energy storage. Inorg. Chem. Front. 5, 999–1015 (2018).

2. Kitchaev, D. A., Dacek, S. T., Sun, W. & Ceder, G. Thermodynamics of Phase Selection

in MnO2 Framework Structures through Alkali Intercalation and Hydration. J. Am. Chem.

Soc. 139, 2672–2681 (2017).

3. Ortiz-Vitoriano, N., Drewett, N. E., Gonzalo, E. & Rojo, T. High performance

manganese-based layered oxide cathodes: overcoming the challenges of sodium ion

batteries. Energy Environ. Sci. 10, 1051–1074 (2017).

4. Energy, U. S. D. of. Energy Explained: Electricity in the United States. (2018). Available

at:

https://www.eia.gov/energyexplained/index.php?page=electricity_in_the_united_states.

(Accessed: 20th July 2018)

5. D. o. E., U. S. Basic Research Needs for Next Generation Electrical Energy Storage.

(2017).

6. Mohamed, A. I. & Whitacre, J. F. Capacity Fade of NaTi2(PO4)3 in Aqueous Electrolyte

Solutions: Relating pH Increases to Long Term Stability. Electrochim. Acta 235, 730–739

(2017).

7. Wu, W., Mohamed, A. & Whitacre, J. F. Microwave Synthesized NaTi2(PO4)3 as an

Aqueous Sodium-Ion Negative Electrode. J. Electrochem. Soc. 160, A497–A504 (2013).

8. Wu, W., Shabhag, S., Chang, J., Rutt, A. & Whitacre, J. F. Relating Electrolyte

Concentration to Performance and Stability for NaTi2(PO4)3/Na0.44MnO2 Aqueous

Sodium-Ion Batteries. J. Electrochem. Soc. 162, A803–A808 (2015).

139

9. Yu, F. et al. Electrochemical characterization of P2-type layered Na2/3Ni1/4Mn3/4O2

cathode in aqueous hybrid sodium/lithium ion electrolyte. Ceram. Int. 43, 9960–9967

(2017).

10. Zhang, H. et al. Towards High-Performance Aqueous Sodium-Ion Batteries: Stabilizing

the Solid/Liquid Interface for NASICON-Type Na2VTi(PO4)3using Concentrated

Electrolytes. ChemSusChem 11, 1382–1389 (2018).

11. Kim, H. et al. Aqueous rechargeable Li and Na ion batteries. Chem. Rev. 114, 11788–

11827 (2014).

12. Greenwood, N. N. & Earnshaw, A. Manganese, Technetium, and Rhenium. in Chemistry

of the Elements 1040–1070 (Butterworth-Heinemann, 1997).

13. Post, J. E. Manganese oxide minerals: Crystal structures and economic and

environmental significance. 96, (1999).

14. Ghodbane, O., Pascal, J. L. & Favier, F. Microstructural effects on charge-storage

properties in MnO 2-based electrochemical supercapacitors. ACS Appl. Mater. Interfaces

1, 1130–1139 (2009).

15. Xiong, P. et al. Redox Active Cation Intercalation/Deintercalation in Two-Dimensional

Layered MnO2Nanostructures for High-Rate Electrochemical Energy Storage. ACS Appl.

Mater. Interfaces 9, 6282–6291 (2017).

16. Zhang, B. et al. An aqueous rechargeable battery based on zinc anode and Na 0.95 MnO

2. Chem. Commun. 50, 1209–1211 (2014).

17. Feng, M. et al. Manganese oxide electrode with excellent electrochemical performance for

sodium ion batteries by pre-intercalation of K and Na ions. Sci. Rep. 7, 2219 (2017).

18. Yan, L. et al. Modulating the electronic structure and pseudocapacitance of δ-MnO 2

140

through transitional metal M (M = Fe, Co and Ni) doping. Electrochim. Acta 306, 529–

540 (2019).

19. Clément, R. J., Bruce, P. G. & Grey, C. P. Review—Manganese-Based P2-Type

Transition Metal Oxides as Sodium-Ion Battery Cathode Materials. J. Electrochem. Soc.

162, A2589–A2604 (2015).

20. Zhu, K. et al. Tunable Electrochemistry via Controlling Lattice Water in Layered Oxides

of Sodium-ion Batteries. ACS Appl. Mater. Interfaces 9, 34909–34914 (2017).

21. Bard, A. J. & Faulkner, L. R. Electrochemical Methods: Fundamentals and Applications.

(John Wiley & Sons, Inc., 2001).

22. Conway, B. E. Electrochemical Supercapacitors: Scientific Fundamentals and

Technological Applications. (Kluwer-Academic, 1999).

23. Mateos, M., Makivic, N., Kim, Y.-S., Limoges, B. & Balland, V. Accessing the two-

electron charge storage capacity of MnO2 in mild aqueous electrolytes. Submitted

2000332, 1–12 (2020).

24. Shan, X. et al. Structural water and disordered structure promote aqueous sodium-ion

energy storage in sodium-birnessite. Nat. Commun. 10, (2019).

25. Shan, X. et al. Framework Doping of Ni Enhances Pseudocapacitive Na-Ion Storage of

(Ni)MnO 2 Layered Birnessite. Cite This Chem. Mater 31, 8786 (2019).

26. Shamoto, M., Tanimoto, T., Tomono, K. & Nakayama, M. EQCM Investigation on

Electrodeposition and Charge Storage Behavior of Birnessite-Type MnO2. ECS Trans. 50,

85–92 (2013).

27. Devaraj, S. & Munichandraiah, N. EQCM Investigation of the Electrodeposition of

MnO[sub 2] and Its Capacitance Behavior. Electrochem. Solid-State Lett. 12, F21 (2009).

141

28. Beasley, C. A., Sassin, M. B. & Long, J. W. Extending Electrochemical Quartz Crystal

Microbalance Techniques to Macroscale Electrodes: Insights on Pseudocapacitance

Mechanisms in MnO x -Coated Carbon Nanofoams . J. Electrochem. Soc. 162, A5060–

A5064 (2015).

29. Yi, F. et al. Investigation on the pseudocapacitive charge storage mechanism of MnO2 in

various electrolytes by electrochemical quartz crystal microbalance (EQCM). Ionics

(Kiel). 25, 2393–2399 (2019).

30. Ma, N. et al. Effect of intercalated alkali ions in layered manganese oxide nanosheets as

neutral electrochemical capacitors. Chem. Commun. 55, 1213–1216 (2019).

31. Zhang, Q. et al. The Charge Storage Mechanisms of 2D Cation-Intercalated Manganese

Oxide in Different Electrolytes. Adv. Energy Mater. 1802707, 1802707 (2018).

32. Simon, P. & Gogotsi, Y. Materials for electrochemical capacitors. Nat. Mater. 7, 845–854

(2008).

33. Brousse, T. et al. Long-term cycling behavior of asymmetric activated carbon/MnO2

aqueous electrochemical supercapacitor. J. Power Sources 173, 633–641 (2007).

34. Barbieri, O., Hahn, M., Herzog, A. & Kötz, R. Capacitance limits of high surface area

activated carbons for double layer capacitors. Carbon N. Y. (2005).

doi:10.1016/j.carbon.2005.01.001

35. Khu, L. Van, Cu, D. Van, Thi, L. & Thuy, T. Investigation of the Capacitive Properties of

Activated Carbon Prepared from Corn Cob in Na 2 SO 4 and K 2 SO 4 Electrolytes. 4,

302–315 (2016).

36. Nybeck, C. N., Dodson, D. A., Wetz, D. A. & Heinzel, J. M. Characterization of

Ultracapacitors for Transient Load Applications. IEEE Trans. Plasma Sci. 47, 2493–2499

142

(2019).

37. Srinivasan, S. & Gileadi, E. The potential-sweep method: A theoretical analysis.

Electrochim. Acta 11, 321–335 (1966).

38. Conway, B. E. & Gileadi, E. Kinetic theory of pseudo-capacitance and electrode reactions

at appreciable surface coverage. Trans. Faraday Soc. 58, 2493–2509 (1962).

39. Fleischmann, S. et al. Pseudocapacitance : From Fundamental Understanding to High

Power Energy Storage Materials. Chem. Rev. (2020). doi:10.1021/acs.chemrev.0c00170

40. Trasatti, S. & Buzzanca, G. Ruthenium dioxide: A new interesting electrode material.

Solid state structure and electrochemical behaviour. J. Electroanal. Chem. 29, A1–A5

(1971).

41. Brousse, T., Bélanger, D. & Long, J. W. To Be or Not To Be Pseudocapacitive? J.

Electrochem. Soc. 162, A5185–A5189 (2015).

42. Okubo, M. et al. Nanosize effect on high-rate Li-ion intercalation in LiCoO2 electrode. J.

Am. Chem. Soc. 129, 7444–7452 (2007).

43. Rauda, I. E. et al. Nanostructured pseudocapacitors based on atomic layer deposition of

V2O5onto conductive nanocrystal-based mesoporous ITO scaffolds. Adv. Funct. Mater.

24, 6717–6728 (2014).

44. Li, X. et al. Impact of the electrode thickness and crystal water to pseudocapacitive

performances of layered birnessite MnO2. Nanotechnology (2020). doi:10.1088/1361-

6528/ab73bf

45. Bunker, B. C. & Casey, W. H. The Structure and Properties of Water. in The Aqueous

Chemistry of Oxides 51–60 (Oxford University Press, 2016).

46. Franks, F. The Solvent Properties of Water. in Water: A Comprehensive Treatise. Volume

143

2 (ed. Franks, F.) 1–54 (Plenum Press, 1973).

47. Bhide, A., Hofmann, J., Dürr, A. K., Janek, J. & Adelhelm, P. Electrochemical stability of

non-aqueous electrolytes for sodium-ion batteries and their compatibility with Na 0.7 CoO

2. Phys. Chem. Chem. Phys. 16, 1987–1998 (2014).

48. Schindler, P. W. & Stumm, W. The Surface Chemistry of Oxides, Hydroxides, and Oxide

Minerals. in Aquatic Surface Chemistry: Chemical Processes at the Particle-Water

Interface (ed. Stumm, W.) 83–110 (John Wiley & Sons, Inc., 1987).

49. Bunker, B. C. & Casey, W. H. The Chemistry of Extended Oxide Surfaces. in The

Aqueous Chemistry of Oxides 132–157 (Oxford University Press, 2016).

50. Westall, J. C. Adsorption Mechanisms in Aquatic Surface Chemistry. in Aquatic Surface

Chemistry: Chemical Processes at the Particle-Water Interface (ed. Stumm, W.) 3–32

(John Wiley & Sons, 1987).

51. Brown, M. A., Goel, A. & Abbas, Z. Effect of Electrolyte Concentration on the Stern

Layer Thickness at a Charged Interface. Angew. Chemie - Int. Ed. 55, 3790–3794 (2016).

52. Suo, L. et al. ‘Water-in-salt’ electrolyte enables high-voltage aqueous lithium-ion

chemistries. Science (80-. ). 350, 938–943 (2015).

53. Wang, F. et al. Stabilizing high voltage LiCoO 2 cathode in aqueous electrolyte with

interphase-forming additive. Energy Environ. Sci. 9, 3666–3673 (2016).

54. Che, H. et al. Electrolyte design strategies and research progress for room-temperature

sodium-ion batteries. Energy Environ. Sci. 10, 1075–1101 (2017).

55. Alvarado, J. et al. Improvement of the Cathode Electrolyte Interphase on P2-Na 2/3 Ni 1/3

Mn 2/3 O 2 by Atomic Layer Deposition. ACS Appl. Mater. Interfaces 9, 26518–26530

(2017).

144

56. Hwang, J.-Y., Myung, S.-T. & Sun, Y.-K. Sodium-ion batteries: present and future. Chem.

Soc. Rev. 46, 3529–3614 (2017).

57. Pourbaix, M. Atlas of electrochemical equilibria in aqueous solutions. in 234–286

(National Association of Corrosion Engineers, 1974).

58. Wang, Y., Lou, J.-Y., Wu, W., Wang, C.-X. & Xia, Y.-Y. Hybrid Aqueous Energy

Storage Cells Using Activated Carbon and Lithium-Ion Intercalated Compounds III.

Capacity Fading Mechanism of LiCo1 ∕ 3Ni1 ∕ 3Mn1 ∕ 3O2 at Different pH Electrolyte

Solutions. J. Electrochem. Soc. 154, A228–A234 (2007).

59. Miyazaki, K. et al. Enhanced resistance to oxidative decomposition of aqueous

electrolytes for aqueous lithium-ion batteries. Chem. Commun. 52, 4979–4982 (2016).

60. Kühnel, R.-S. et al. “Water-in-salt” electrolytes enable the use of cost-effective aluminum

current collectors for aqueous high-voltage batteries. Chem. Commun. 52, 10435–10438

(2016).

61. Tomiyasu, H. et al. An aqueous electrolyte of the widest potential window and its superior

capability for capacitors. Sci. Rep. 7, 45048 (2017).

62. Suo, L. et al. “Water-in-Salt” Electrolyte Makes Aqueous Sodium-Ion Battery Safe,

Green, and Long-Lasting. Adv. Energy Mater. 7, 1701189 (2017).

63. Kühnel, R.-S., Reber, D. & Battaglia, C. A High-Voltage Aqueous Electrolyte for

Sodium-Ion Batteries. ACS Energy Lett. 2, 2005–2006 (2017).

64. Zhao, J. et al. High-voltage Zn/LiMn0.8Fe0.2PO4 aqueous rechargeable battery by virtue

of ‘water-in-salt’ electrolyte. Electrochem. commun. 69, 6–10 (2016).

65. Nakamoto, K., Kano, Y., Kitajou, A. & Okada, S. Electrolyte dependence of the

performance of a Na2FeP2O7//NaTi2(PO4)3 rechargeable aqueous sodium-ion battery. J.

145

Power Sources 327, 327–332 (2016).

66. Luo, J.-Y., Cui, W.-J., He, P. & Xia, Y.-Y. Raising the cycling stability of aqueous

lithium-ion batteries by eliminating oxygen in the electrolyte. Nat. Chem. 2, 760–765

(2010).

67. Hou, Z. et al. Surfactant widens the electrochemical window of an aqueous electrolyte for

better rechargeable aqueous sodium/zinc battery. J. Mater. Chem. A 5, 730–738 (2017).

68. Harivignesh, R. et al. Cu-doped P2-Na0.5Ni0.33Mn0.67O2 encapsulated with MgO as

novel high voltage cathode with enhanced Na-storage properties. J. Mater. Chem. A 5,

8408–8415 (2017).

69. Suo, L. et al. Advanced High-Voltage Aqueous Lithium-Ion Battery Enabled by “Water-

in-Bisalt” Electrolyte. Angew. Chemie - Int. Ed. 55, 7136–7141 (2016).

70. Guo, Z. et al. Multi-functional Flexible Aqueous Sodium-Ion Batteries with High Safety.

Chem 3, 348–362 (2017).

71. Zhang, X. et al. Na-birnessite with high capacity and long cycle life for rechargeable

aqueous sodium-ion battery cathode electrodes. J. Mater. Chem. A 4, 856–860 (2016).

72. Intercalation Chemistry. (Academic Press, Inc., 1982).

73. Bunker, B. C. & Casey, W. H. Solvated Ions in Water. in The Aqueous Chemistry of

Oxides 61–86 (Oxford University Press, 2016).

74. Bockris, J. O., Reddy, A. K. N. & Gamboa-Aldeco, M. Ion-Solvent Interactions. in

Modern Electrochemistry, Volume 1, Ionics 45–174 (Springer, 2002).

75. Nightingale, E. R. Phenomenological theory of ion solvation. Effective radii of hydrated

ions. J. Phys. Chem. 63, 1381–1387 (1959).

76. Qu, Q. T. et al. Study on electrochemical performance of activated carbon in aqueous

146

Li2SO4, Na2SO4 and K2SO4 electrolytes. Electrochem. commun. 10, 1652–1655 (2008).

77. Chen, D. et al. Probing the Charge Storage Mechanism of a Pseudocapacitive MnO2

Electrode Using in Operando Raman Spectroscopy. Chem. Mater. 27, 6608–6619 (2015).

78. Shao, J., Li, X., Qu, Q. & Wu, Y. Study on different power and cycling performance of

crystalline KxMnO 2·nH 2O as cathode material for supercapacitors in Li2SO4, Na 2SO

4, and K 2SO 4 aqueous electrolytes. J. Power Sources 223, 56–61 (2013).

79. Eliad, L., Salitra, G., Soffer, A. & Aurbach, D. Ion sieving effects in the electrical double

layer of porous carbon electrodes: Estimating effective ion size in electrolytic solutions. J.

Phys. Chem. B 105, 6880–6887 (2001).

80. Lee, H. Y. & Goodenough, J. B. Supercapacitor Behavior with KCl Electrolyte. J. Solid

State Chem. 144, 220–223 (1999).

81. Young, M. J., Holder, A. M., George, S. M. & Musgrave, C. B. Charge storage in cation

incorporated α-MnO2. Chem. Mater. 27, 1172–1180 (2015).

82. Lucht, K. P. & Mendoza-Cortes, J. L. Birnessite: A Layered Manganese Oxide To

Capture Sunlight for Water-Splitting Catalysis. (2015). doi:10.1021/acs.jpcc.5b07860

83. Suss, M. E. & Presser, V. Water Desalination with Energy Storage Electrode Materials.

Joule 2, 10–15 (2018).

84. Byles, B. W., Hayes-Oberst, B. & Pomerantseva, E. Ion Removal Performance,

Structural/Compositional Dynamics, and Electrochemical Stability of Layered Manganese

Oxide Electrodes in Hybrid Capacitive Deionization. ACS Appl. Mater. Interfaces 10,

32313–32322 (2018).

85. Leong, Z. Y. & Yang, H. Y. A Study of MnO2 with Different Crystalline Forms for

Pseudocapacitive Desalination. ACS Appl. Mater. Interfaces 11, 13176–13184 (2019).

147

86. Peng, Q. et al. Cadmium Removal from Aqueous Solution by a Deionization

Supercapacitor with a Birnessite Electrode. ACS Appl. Mater. Interfaces 8, 34405–34413

(2016).

87. Srimuk, P., Su, X., Yoon, J., Aurbach, D. & Presser, V. Charge-transfer materials for

electrochemical water desalination, ion separation and the recovery of elements. Nature

Reviews Materials 5, (2020).

88. Devaraj, S. & Munichandraiah, N. Effect of crystallographic structure of MnO2 on its

electrochemical capacitance properties. J. Phys. Chem. C 112, 4406–4417 (2008).

89. Potter, R. M. & Rossman, G. R. The tetravalent manganese oxides: identification,

hydration, and structural relationships by infrared spectroscopy. Am. Mineral. 64, 1199

(1979).

90. Lopano, C. L., Heaney, P. J., Post, J. E., Hanson, J. & Komarneni, S. Time-resolved

structural analysis of K- and Ba-exchange reactions with synthetic Na-birnessite using

synchrotron X-ray diffraction. Am. Mineral. 92, 380–387 (2007).

91. Shen, X. F. et al. Control of nanometer-scale tunnel sizes of porous manganese oxide

octahedral molecular sieve nanomaterials. Adv. Mater. 17, 805–809 (2005).

92. Lin, H. Y. et al. Factors influencing the structure of electrochemically prepared α-MnO2

and γ-MnO2 phases. Electrochim. Acta 52, 6548–6553 (2007).

93. Birkner, N. & Navrotsky, A. Thermodynamics of manganese oxides: Sodium, potassium,

and calcium birnessite and cryptomelane. Proc. Natl. Acad. Sci. 114, E1046–E1053

(2017).

94. Chen, B. R. et al. Understanding crystallization pathways leading to manganese oxide

polymorph formation. Nat. Commun. 9, (2018).

148

95. Komaba, S., Yabuuchi, N. & Tsuchikawa, T. Interfacial Charge Storage of Manganese

Oxide Electrodes for. in Electrical Phenomena at Interfaces and Biointerfaces:

Fundamentals and Applications in Nano-, Bio-, and Environmental Sciences (ed.

Ohshima, H.) 491–507 (John Wiley & Sons, Inc., 2012).

96. Wu, T. H. et al. Charge storage mechanism of activated manganese oxide composites for

pseudocapacitors. J. Mater. Chem. A 3, 12786–12795 (2015).

97. Shafi, P. M., Dhanabal, R., Chithambararaj, A., Velmathi, S. & Bose, A. C. α-MnO 2 /h-

MoO 3 Hybrid Material for High Performance Supercapacitor Electrode and

Photocatalyst. ACS Sustain. Chem. Eng. 5, 4757–4770 (2017).

98. Young, M. J., Holder, A. M. & Musgrave, C. B. The Unified Electrochemical Band

Diagram Framework: Understanding the Driving Forces of Materials Electrochemistry.

Adv. Funct. Mater. 28, 1–19 (2018).

99. Ragupathy, P., Vasan, H. N. & Munichandraiah, N. Synthesis and Characterization of

Nano-MnO2 for Electrochemical Supercapacitor Studies. J. Electrochem. Soc. 155, A34–

A40 (2008).

100. Byles, B. W., Palapati, N. K. R., Subramanian, A. & Pomerantseva, E. The role of

electronic and ionic conductivities in the rate performance of tunnel structured manganese

oxides in Li-ion batteries. APL Mater. 4, 046108 (2016).

101. Whitacre, J. F. et al. An aqueous electrolyte, sodium ion functional, large format energy

storage device for stationary applications. J. Power Sources 213, 255–264 (2012).

102. Kim, S. et al. Direct Observation of an Anomalous Spinel-to-Layered Phase Transition

Mediated by Crystal Water Intercalation. Angew. Chemie - Int. Ed. 54, 15094–15099

(2015).

149

103. Kim, S. et al. On the Mechanism of Crystal Water Insertion during Anomalous Spinel-to-

Birnessite Phase Transition. Chem. Mater. 28, 5488–5494 (2016).

104. Lanson, B., Drits, V.A., Feng, Q., et Manceau, A. Crystal Structure Determination of

Synthetic Na-Rich Birnessite: Evidence for a Triclinic One-Layer Cell. Am. Mineral. 87,

1662–1671 (2002).

105. Renuka, R. & Ramamurthy, S. Investigation on layered birnessite type manganese oxides

for battery applications. J. Power Sources 87, 144–152 (2000).

106. Sun, X., Duffort, V., Mehdi, B. L., Browning, N. D. & Nazar, L. F. Investigation of the

Mechanism of Mg Insertion in Birnessite in Nonaqueous and Aqueous Rechargeable Mg-

Ion Batteries. Chem. Mater. 28, 534–542 (2016).

107. Qiu, N., Chen, H., Yang, Z., Sun, S. & Wang, Y. Low-cost birnessite as a promising

cathode for high-performance aqueous rechargeable batteries. Electrochim. Acta 272,

154–160 (2018).

108. Oscarson, D. W., Huang, P. M., Liaw, W. K. & Hammer, U. T. Kinetics of Oxidation of

Arsenite by Various Manganese Dioxides. Soil Sci. Soc. Am. J. 47, 644–648 (1983).

109. Wang, Y., Zhang, Y.-Z., Gao, Y.-Q., Sheng, G. & Ten Elshof, J. E. Defect engineering of

MnO 2 nanosheets by substitutional doping for printable solid-state micro-

supercapacitors. Nano Energy 68, 104306 (2020).

110. Gao, P. et al. The critical role of point defects in improving the specific capacitance of Î-

MnO 2 nanosheets. Nat. Commun. 8, 14559 (2017).

111. Pinaud, B. A., Chen, Z., Abram, D. N. & Jaramillo, T. F. Thin films of sodium birnessite-

type MnO2: Optical properties, electronic band structure, and solar photoelectrochemistry.

J. Phys. Chem. C 115, 11830–11838 (2011).

150

112. Lee, S. W., Kim, J., Chen, S., Hammond, P. T. & Shao-Horn, Y. Carbon

Nanotube/Manganese Oxide Ultrathin Film Electrodes for Electrochemical Capacitors.

Am. Chem. Soc. 4, 3889–3896 (2010).

113. Yadav, G. G. et al. Regenerable Cu-intercalated MnO 2 layered cathode for highly

cyclable energy dense batteries. Nat. Commun. 8, 1–9 (2017).

114. Arias, C. R. et al. New insights into pseudocapacitive charge-storage mechanisms in Li-

birnessite type MnO2 monitored by fast quartz crystal microbalance methods. J. Phys.

Chem. C 118, 26551–26559 (2014).

115. Toupin, M., Brousse, T. & Bélanger, D. Influence of microstucture on the charge storage

properties of chemically synthesized manganese dioxide. Chem. Mater. 14, 3946–3952

(2002).

116. Costentin, C., Porter, T. R. & Savéant, J. M. How Do Pseudocapacitors Store Energy?

Theoretical Analysis and Experimental Illustration. ACS Appl. Mater. Interfaces 9, 8649–

8658 (2017).

117. Cox, P. A. Introduction. in Transition Metal Oxides: An Introduction to their Electronic

Structure and Properties (eds. Rowlinson, J. S., Halpern, J., Green, M. L. H. &

Mukaiyama, T.) 1–32 (Oxford University Press, 1992).

118. Muller, U. Linked Polyhedra. in Inorganic Structural Chemistry (eds. Woollins, D.,

Crabtree, B., Atwood, D. & Meyre, G.) 166–189 (John Wiley & Sons, Ltd., 2007).

119. Mendiboure, A., Delmas, C. & Hagenmuller, P. Electrochemical Intercalation and

Deintercalation of NaxMnOz Bronzes. JOURNAL OF SOLID STATE CHEMISTRY 57,

(1985).

120. Athouël, L. et al. Variation of the MnO2 birnessite structure upon charge/discharge in an

151

electrochemical supercapacitor electrode in aqueous Na2SO 4 electrolyte. J. Phys. Chem.

C 112, 7270–7277 (2008).

121. Yang, L. et al. Investigation into the origin of high stability of δ-MnO 2 pseudo-capacitive

electrode using operando Raman spectroscopy. Nano Energy (2016).

doi:10.1016/j.nanoen.2016.10.018

122. Kanoh, H., Tang, W., Makita, Y. & Ooi, K. Electrochemical intercalation of alkali-metal

ions into birnessite-type manganese oxide in aqueous solution. Langmuir 13, 6845–6849

(1997).

123. Beasley, C. A., Sassin, M. B. & Long, J. W. Extending Electrochemical Quartz Crystal

Microbalance Techniques to Macroscale Electrodes: Insights on Pseudocapacitance

Mechanisms in MnO x -Coated Carbon Nanofoams. J. Electrochem. Soc. 162, A5060–

A5064 (2015).

124. Theses, M. & Vergeer, K. A. Trace: Tennessee Research and Creative Exchange

Adsorption of Antimony by Birnessite and the Impact of Antimony on the Electrostatic

Surface Properties of Variable-Charge Soil Minerals. (2013).

125. Zhong, L., Yang, J., Liu, L. & Xing, B. Oxidation of Cr(III) on birnessite surfaces: The

effect of goethite and kaolinite. J. Environ. Sci. (China) 37, 8–14 (2015).

126. Absus, S. et al. A facile synthesis of octahedral layered birnessite-type manganese oxide

(OL-1) nanostructures with tremendous catalytic activity for methylene blue degradation.

in AIP Conference Proceedings 2049, 20108 (2018).

127. Chomkhuntod, P. et al. The Influence of Hydration Energy on Alkali-Earth Intercalated

Layered Manganese Oxides as Electrochemical Capacitors. ACS Appl. Energy Mater.

(2019). doi:10.1021/acsaem.9b01822

152

128. Said, M. I. Akhtenskite-nsutite phases: Polymorphic transformation, thermal behavior and

magnetic properties. J. Alloys Compd. 819, (2020).

129. Simon, D. E., Morton, R. W. & Gislason, J. J. A close look at electrolytic manganese

dioxide (EMD) and the γ-MnO2 & ε-Mno2 phases using rietveld modeling. Adv. X-ray

Anal. 47, 267–280 (2004).

130. Dupont, M. F. & Donne, S. W. Faradaic and Non-Faradaic Contributions to the Power and

Energy Characteristics of Electrolytic Manganese Dioxide for Electrochemical Capacitors.

J. Electrochem. Soc. 163, A888–A897 (2016).

131. Tevar, A. D. & Whitacre, J. F. Relating Synthesis Conditions and Electrochemical

Performance for the Sodium Intercalation Compound Na4Mn9O18 in Aqueous

Electrolyte. J. Electrochem. Soc. 157, A870–A875 (2010).

132. Mortemard de Boisse, B., Carlier, D., Guignard, M. & Delmas, C. Structural and

Electrochemical Characterizations of P2 and New O3-NaxMn1-yFeyO2 Phases Prepared

by Auto-Combustion Synthesis for Na-Ion Batteries. J. Electrochem. Soc. 160, A569–

A574 (2013).

133. Thorne, J. S., Dunlap, R. A. & Obrovac, M. N. Structure and Electrochemistry of

NaxFexMn1-xO2 (1.0 <= x <= 0.5) for Na-Ion Battery Positive Electrodes. J.

Electrochem. Soc. 160, A361–A367 (2012).

134. Xu, S. et al. Fe-Based Tunnel-Type Na0.61[Mn0.27Fe0.34Ti0.39]O2 Designed by a New

Strategy as a Cathode Material for Sodium-Ion Batteries. Adv. Energy Mater. 5, 1–9

(2015).

135. Zheng, L., Li, J. & Obrovac, M. N. Crystal Structures and Electrochemical Performance

of Air-Stable Na 2/3 Ni 1/3-x Cu x Mn 2/3 O 2 in Sodium Cells. Chem. Mater. 29, 1623–

153

1631 (2017).

136. Duffort, V., Talaie, E., Black, R. & Nazar, L. F. Uptake of CO 2 in Layered P2-Na 0.67

Mn 0.5 Fe 0.5 O 2 : Insertion of Carbonate Anions. Chem. Mater. 27, 2515–2524 (2015).

137. Lu, Z. & Dahn, J. R. Intercalation of Water in P2, T2 and O2 Structure AzCoxNi1/3-

xMn2/3O2. Chem. Mater. 13, 1252–1257 (2001).

138. Sathiya, M., Hemalatha, K., Ramesha, K., Tarascon, J.-M. & Prakash, A. S. Synthesis,

Structure, and Electrochemical Properties of the Layered Sodium Insertion Cathode

Material: NaNi1/3Mn1/3Co1/3O2. Chem. Mater. 24, 1846−1853 (2012).

139. Hou, Z., Li, X., Liang, J., Zhu, Y. & Qian, Y. An aqueous rechargeable sodium ion battery

based on a NaMnO2–NaTi2(PO4)3 hybrid system for stationary energy storage. J. Mater.

Chem. A 3, 1400–1404 (2015).

140. Buchholz, D., Chagas, L. G., Vaalma, C., Wu, L. & Passerini, S. Water sensitivity of

layered P2/P3-NaxNi0.22Co0.11Mn0.66O2 cathode material. J. Mater. Chem. A 2,

13415–13421 (2014).

141. Li, Z., Young, D., Xiang, K., Carter, W. C. & Chiang, Y. Towards High Power High

Energy Aqueous Sodium-Ion Batteries: The NaTi 2 (PO 4 ) 3 /Na 0.44 MnO 2 System.

Adv. Energy Mater. 3, 290–294 (2013).

142. Wang, Y. et al. A Novel High Capacity Positive Electrode Material with Tunnel-Type

Structure for Aqueous Sodium-Ion Batteries. Adv. Energy Mater. 5, 1501005 (2015).

143. Chen, F., Huang, Y., Guo, L., Ding, M. & Yang, H. Y. A dual-ion electrochemistry

deionization system based on AgCl-Na 0.44 MnO 2 electrodes. Nanoscale 9, 10101–10108

(2017).

144. Whitacre, J. F., Tevar, A. & Sharma, S. Na4Mn9O18 as a positive electrode material for

154

an aqueous electrolyte sodium-ion energy storage device. Electrochem. commun. 12, 463–

466 (2010).

145. Sauvage, F., Baudrin, E. & Tarascon, J. M. Study of the potentiometric response towards

sodium ions of Na0.44-xMnO2 for the development of selective sodium ion sensors.

Sensors Actuators, B Chem. 120, 638–644 (2007).

146. Wang, Y. et al. Ti-substituted tunnel-type Na0.44MnO2 oxide as a negative electrode for

aqueous sodium-ion batteries. Nat. Commun. 6, 1–10 (2015).

147. Pang, G. et al. Enhanced Performance of Aqueous Sodium-Ion Batteries Using Electrodes

Based on the NaTi 2 (PO 4 ) 3 /MWNTs-Na 0.44 MnO 2 System. Energy Technol. 2,

705–712 (2014).

148. Yao, H. et al. Designing Air-Stable O3-Type Cathode Materials by Combined Structure

Modulation for Na-Ion Batteries. J. Am. Chem. Soc. 139, 8440–8443 (2017).

149. Deng, J. et al. High Energy Density Sodium-Ion Battery with Industrially Feasible and

Air-Stable O3-Type Layered Oxide Cathode. Adv. Energy Mater. 1701610, 1701610

(2017).

150. Mu, L. et al. Prototype Sodium-Ion Batteries Using an Air-Stable and Co/Ni-Free O3-

Layered Metal Oxide Cathode. Adv. Mater. 27, 6928–6933 (2015).

151. Delmas, C., Fouassier, C. & Hagenmuller, P. Structural classification and properties of the

layered oxides. Phys. B+C 99, 81–85 (1980).

152. Caballero, A. et al. Synthesis and characterization of high-temperature hexagonal P2-

Na0.6 MnO2 and its electrochemical behaviour as cathode in sodium cells. J. Mater.

Chem. 12, 1142–1147 (2002).

153. Li, Y. et al. Air-Stable Copper-Based P2-Na 7/9 Cu 2/9 Fe 1/9 Mn 2/3 O 2 as a New

155

Positive Electrode Material for Sodium-Ion Batteries. Adv. Sci. 2, 1500031 (2015).

154. Han, M. H. et al. Moisture exposed layered oxide electrodes as Na-ion battery cathodes. J.

Mater. Chem. A 4, 18963–18975 (2016).

155. Han, M. H. et al. High-Performance P2-Phase Na2/3Mn0.8Fe0.1Ti0.1O2 Cathode

Material for Ambient-Temperature Sodium-Ion Batteries. Chem. Mater. 28, 106–116

(2016).

156. Eriksson, T. A. et al. Influence of Substitution on the Structure and Electrochemistry of

Layered Manganese Oxides. Chem. Mater. 15, 4456–4463 (2003).

157. Buchholz, D. et al. Toward Na-ion Batteries-Synthesis and Characterization of a Novel

High Capacity Na Ion Intercalation Material. Chem. Mater. 25, 142–148 (2013).

158. Stone, A. T. & Morgan, J. J. Reductive Dissolution of Metal Oxides. in Aquatic Surface

Chemistry: Chemical Processes at the Particle-Water Interface (ed. Stumm, W.) 221–254

(John Wiley & Sons, Inc., 1987).

159. Liu, Y. et al. Hollow K0.27MnO2 Nanospheres as Cathode for High-Performance

Aqueous Sodium Ion Batteries. ACS Appl. Mater. Interfaces 8, 14564–14571 (2016).

160. Kang, W. et al. P2-type NaxCu0.15Ni0.20Mn0.65O2 cathodes with high voltage for high-

power and long-life sodium-ion batteries. ACS Appl. Mater. Interfaces 8, 31661–31668

(2016).

161. Venkatesh, G., Kishore, B., Viswanatha, R., Aurbach, D. & Munichandraiah, N. P2-Type

Na 0.67 Mn 0.65 Fe 0.20 Ni 0.15 O 2 Microspheres as a Positive Electrode Material with a

Promising Electrochemical Performance for Na-Ion Batteries. J. Electrochem. Soc. 164,

A2176–A2182 (2017).

162. Zhang, Q. et al. Structural Insight into Layer Gliding and Lattice Distortion in Layered

156

Manganese Oxide Electrodes for Potassium-Ion Batteries. Adv. Energy Mater. 9, 1–9

(2019).

163. Bai, P. et al. Ni-Doped Layered Manganese Oxide as A Stable Cathode for Potassium Ion

Batteries. ACS Appl. Mater. Interfaces (2020). doi:10.1021/acsami.9b22237

164. Kang, W. et al. Copper substituted P2-type Na0.67CuxMn1-xO2: A stable high-power

sodium-ion battery cathode. J. Mater. Chem. A 3, 22846–22852 (2015).

165. Wang, L. et al. Copper-Substituted Na0.67Ni0.3-xCuxMn0.7O2 Cathode Materials for

Sodium-Ion Batteries with Suppressed P2-O2 Phase Transition. J. Mater. Chem. A 5,

8752–8761 (2017).

166. Liu, N. et al. Large-area atomically thin MoS2 nanosheets prepared using electrochemical

exfoliation. ACS Nano 8, 6902–6910 (2014).

167. Ambrosi, A. & Pumera, M. Electrochemical Exfoliation of MoS2 Crystal for Hydrogen

Electrogeneration. Chem. - A Eur. J. 24, 18551–18555 (2018).

168. Achee, T. C. et al. High-yield scalable graphene nanosheet production from compressed

graphite using electrochemical exfoliation. Sci. Rep. 8, 1–8 (2018).

169. Kai, K. et al. Room-temperature synthesis of manganese oxide monosheets. J. Am. Chem.

Soc. 130, 15938–15943 (2008).

170. Cui, Y., Liu, Z.-H., Wang, M. & Ooi, K. New Approach to the Delamination of Layered

Manganese Oxide. Chem. Lett. 35, (2006).

171. Ma, B., Hou, W., Han, Y., Sun, R. & Liu, Z. H. Exfoliation reaction of birnessite-type

manganese oxide by a host-guest electrostatic repulsion in aqueous solution. Solid State

Sci. 10, 141–147 (2008).

172. Liu, Z., Ma, R., Ebina, Y., Takada, K. & Sasaki, T. Synthesis and delamination of layered

157

manganese oxide nanobelts. Chem. Mater. 19, 6504–6512 (2007).

173. Maluangnont, T. et al. Osmotic swelling of layered compounds as a route to producing

high-quality two-dimensional materials. A comparative study of tetramethylammonium

versus tetrabutylammonium cation in a lepidocrocite-type titanate. Chem. Mater. 25,

3137–3146 (2013).

174. Kim, H.-S. et al. Oxygen vacancies enhance pseudocapacitive charge storage properties of

MoO3−x. Nat. Mater. 16, 454–460 (2016).

175. Charles, D. S. et al. Structural water engaged disordered vanadium oxide nanosheets for

high capacity aqueous potassium-ion storage. Nat. Commun. 8, 15520 (2017).

176. Li, S. et al. Design of V2O5·xH2O cathode for highly enhancing sodium storage. J. Alloys

Compd. 722, 278–286 (2017).

177. Wei, Q. et al. Hydrated vanadium pentoxide with superior sodium storage capacity. J.

Mater. Chem. A 3, 8070–8075 (2015).

178. Mitchell, J. B., Lo, W. C., Genc, A., Lebeau, J. & Augustyn, V. Transition from Battery to

Pseudocapacitor Behavior via Structural Water in Tungsten Oxide. Chem. Mater. 29,

3928–3937 (2017).

179. Mitchell, J. B. et al. Confined Interlayer Water Promotes Structural Stability for High-

Rate Electrochemical Proton Intercalation in Tungsten Oxide Hydrates. ACS Energy Lett.

4, 2805–2812 (2019).

180. Li, Y. et al. From α-NaMnO 2 to crystal water containing Na-birnessite: enhanced cycling

stability for sodium-ion batteries. CrystEngComm 18, 3136–3141 (2016).

181. Sai Gautam, G., Canepa, P., Richards, W. D., Malik, R. & Ceder, G. Role of Structural

H2O in Intercalation Electrodes: The Case of Mg in Nanocrystalline Xerogel-V2O5. Nano

158

Lett. 16, acs.nanolett.5b05273 (2016).

182. Sahadeo, E. et al. Investigation of the water-stimulated Mg2+ insertion mechanism in an

electrodeposited MnO2 cathode using X-ray photoelectron spectroscopy. Phys. Chem.

Chem. Phys. 20, 2517–2526 (2018).

183. Grey, C. P. & Tarascon, J. M. Sustainability and in situ monitoring in battery

development. Nat. Mater. 16, 45–56 (2016).

184. Lu, Z. & Dahn, J. R. In Situ X-Ray Diffraction Study of P2-Na2/3Ni1/3Mn2/3O2. J.

Electrochem. Soc. 148, A1225–A1229 (2001).

185. Lee, D. H., Xu, J. & Meng, Y. S. An advanced cathode for Na-ion batteries with high rate

and excellent structural stability. Phys. Chem. Chem. Phys. 15, 3304–3312 (2013).

186. De La Llave, E. et al. Improving Energy Density and Structural Stability of Manganese

Oxide Cathodes for Na-Ion Batteries by Structural Lithium Substitution. Chem. Mater. 28,

9064–9076 (2016).

187. Zhang, Y., Ye, K., Cheng, K., Wang, G. & Cao, D. Three-dimensional lamination-like P2-

Na2/3Ni1/3Mn2/3O2 assembled with two-dimensional ultrathin nanosheets as the cathode

material of an aqueous capacitor battery. Electrochim. Acta 148, 195–202 (2014).

188. Borodin, O. et al. Liquid Structure with Nano-Heterogeneity Promotes Cationic Transport

in Concentrated Electrolytes. ACS Nano 11, 10462–10471 (2017).

189. Byles, B. W., Cullen, D. A., More, K. L. & Pomerantseva, E. Tunnel structured

manganese oxide nanowires as redox active electrodes for hybrid capacitive deionization.

Nano Energy 44, 476–488 (2018).

190. Kuo, S.-L. & Wu, N.-L. Investigation of Pseudocapacitive Charge-Storage Reaction of

MnO2⋅nH2O Supercapacitors in Aqueous Electrolytes. J. Electrochem. Soc. 153, A1317–

159

A1324 (2006).

191. Abou-El-Sherbini, K. S., Askar, M. H. & Schöllhorn, R. Hydrated layered manganese

dioxide: Part I. Synthesis and characterization of some hydrated layered manganese

dioxides from α-NaMnO2. Solid State Ionics 150, 407–415 (2002).

192. Lu, Z., Donaberger, R. A. & Dahn, J. R. Superlattice ordering of Mn, Ni, and Co in

layered alkali transition metal oxides with P2, P3, and O3 structures. Chem. Mater. 12,

3583–3590 (2000).

193. Shannon, R. D. Revised Effective Ionic Radii and Systematic Studies of Interatomie

Distances in Halides and Chaleogenides. Acta Cryst 32, 751–767 (1976).

194. Nam, K. W. et al. Critical role of crystal water for a layered cathode material in sodium

ion batteries. Chem. Mater. 27, 3721–3725 (2015).

195. Yuan, D. et al. P2-type Na0.67Mn0.65Fe0.2Ni 0.15O2 Cathode Material with High-

capacity for Sodium-ion Battery. Electrochim. Acta 116, 300–305 (2014).

196. Chagas, L. G., Buchholz, D., Vaalma, C., Wu, L. & Passerini, S. P-type

NaxNi0.22Co0.11Mn0.66O2 materials: linking synthesis with structure and

electrochemical performance. J. Mater. Chem. A 2, 20263–20270 (2014).

197. Talaie, E., Duffort, V., Smith, H. L., Fultz, B. & Nazar, L. F. Structure of the high voltage

phase of layered P2-Na 2/3−z [Mn 1/2 Fe 1/2 ]O 2 and the positive effect of Ni substitution on

its stability. Energy Environ. Sci. 8, 2512–2523 (2015).

198. Mortemard De Boisse, B., Carlier, D., Guignard, M., Bourgeois, L. & Delmas, C. P2-

NaxMn1/2Fe1/2O2 phase used as positive electrode in Na batteries: Structural changes

induced by the electrochemical (De)intercalation process. Inorg. Chem. 53, 11197–11205

(2014).

160

199. Talaie, E., Kim, S. Y., Chen, N. & Nazar, L. F. Structural Evolution and Redox Processes

Involved in the Electrochemical Cycling of P2–Na 0.67 [Mn 0.66 Fe 0.20 Cu 0.14 ]O 2.

Chem. Mater. 29, 6684–6697 (2017).

200. Liu, L. et al. High-Performance P2-Type Na2/3(Mn1/2Fe1/4Co1/4)O2Cathode Material

with Superior Rate Capability for Na-Ion Batteries. Adv. Energy Mater. 5, 1500944

(2015).

201. Yuan, C. et al. Investigation of the intercalation of polyvalent cations (Mg2+, Zn2+) into

λ-MnO2for rechargeable aqueous battery. Electrochim. Acta 116, 404–412 (2014).

202. Largeot, C. et al. Relation between the Ion Size and Pore Size for an Electric Double-

Layer Capacitor. J. Am. Chem. Soc. 130, 2730–2731 (2008).

203. Augustyn, V., Simon, P. & Dunn, B. Pseudocapacitive oxide materials for high-rate

electrochemical energy storage. Energy Environ. Sci. 7, 1597–1614 (2014).

204. Choi, C. et al. Achieving high energy density and high power density with

pseudocapacitive materials. Nat. Rev. Mater. (2019). doi:10.1038/s41578-019-0142-z

205. Rauda, I. E. et al. Nanostructured Pseudocapacitors Based on Atomic Layer Deposition of

V2O5 onto Conductive Nanocrystal-based Mesoporous ITO Scaffolds. Adv. Funct. Mater.

24, 6717–6728 (2014).

206. Augustyn, V. & Gogotsi, Y. 2D Materials with Nanoconfined Fluids for Electrochemical

Energy Storage. Joule 1, 443–452 (2017).

207. Palacín, M. R., Simon, P. & Tarascon, J. M. Nanomaterials for Electrochemical Energy

Storage : the Good and the Bad. Acta Chim. Slov. 63, 417–423 (2016).

208. Wang, R. et al. Operando Atomic Force Microscopy Reveals Mechanics of Structural

Water Driven Battery-to-Pseudocapacitor Transition. ACS Nano 12, 6032–6039 (2018).

161

209. Wu, T., Zhu, K., Qin, C. & Huang, K. Unraveling the role of structural water in bilayer

V2O5 during Zn2+-intercalation: Insights from DFT calculations. J. Mater. Chem. A 7,

5612–5620 (2019).

210. Liu, Z. et al. Performance Modulation through Synergetic Effect of Interstitial Water with

Ti-substitution for Sodium Ion Battery Cathode. Chem. Lett 48, 670–673 (2019).

211. Yabuuchi, N. et al. New O2/P2-type Li-excess layered manganese oxides as promising

multi-functional electrode materials for rechargeable Li/Na batteries. Advanced Energy

Materials (2014). doi:10.1002/aenm.201301453

212. Clement, R. J. et al. Structurally stable Mg-doped P2-Na 2/3 Mn 1-y Mg y O 2 sodium-

ion battery cathodes with high rate performance: insights from electrochemical, NMR and

diffraction studies. Energy Environ. Sci. Energy Environ. Sci 3240, 3240–3251 (2016).

213. Liu, C. ling, Luo, S. hua, Huang, H. bo, Zhai, Y. chun & Wang, Z. wen. Layered

potassium-deficient P2- and P3-type cathode materials KxMnO2 for K-ion batteries.

Chem. Eng. J. 356, 53–59 (2019).

214. Boyd, S., Dhall, R., LeBeau, J. M. & Augustyn, V. Charge storage mechanism and

degradation of P2-type sodium transition metal oxides in aqueous electrolytes. J. Mater.

Chem. A 6, 22266–22276 (2018).

215. Ashiotis, G. et al. The fast azimuthal integration Python library: pyFAI. J. Appl. Cryst 48,

510–519 (2015).

216. Cao, C., Shyam, B., Stone, K. H. & Toney, M. F. In Situ Study of Silicon Electrode

Lithiation with X-ray Reflectivity. Nano Lett. (2016). doi:10.1021/acs.nanolett.6b02926

217. Brousse, T. et al. Crystalline MnO[sub 2] as Possible Alternatives to Amorphous

Compounds in Electrochemical Supercapacitors. J. Electrochem. Soc. 153, A2171–A2180

162

(2006).

218. Ghodbane, O., Ataherian, F., Wu, N. L. & Favier, F. In situ crystallographic investigations

of charge storage mechanisms in MnO2-based electrochemical capacitors. J. Power

Sources 206, 454–462 (2012).

219. Li, Y. et al. Air-Stable Copper-Based P2-Na 7/9 Cu 2/9 Fe 1/9 Mn 2/3 O 2 as a New

Positive Electrode Material for Sodium-Ion Batteries. Adv. Sci. 2, 1500031 (2015).

220. Yao, M. et al. Simple and Cost-Effective Approach to Dramatically Enhance the

Durability and Capability of a Layered δ-MnO 2 Based Electrode for Pseudocapacitors: A

Practical Electrochemical Test and Mechanistic Revealing. ACS Appl. Energy Mater. 2,

2743–2750 (2019).

221. Chen, T. et al. Benefits of Copper and Magnesium Co-substitution in

Na0.5Mn0.6Ni0.4O2 as a Superior Cathode for Sodium-Ion Batteries. ACS Appl. Energy

Mater. acsaem.8b01909 (2018). doi:10.1021/acsaem.8b01909

222. Dupont, M. F., Forghani, M., Cameron, A. P. & Donne, S. W. Effect of electrolyte cation

on the charge storage mechanism of manganese dioxide for electrochemical capacitors.

Electrochim. Acta 271, 337–350 (2018).

223. Phadke, S., Mysyk, R. & Anouti, M. Effect of cation (Li+, Na+, K+, Rb+, Cs+) in

aqueous electrolyte on the electrochemical redox of Prussian blue analogue (PBA)

cathodes. J. Energy Chem. (2020). doi:10.1016/j.jechem.2019.01.025

224. Shao, J., Li, X., Qu, Q. & Wu, Y. Study on different power and cycling performance of

crystalline K xMnO 2·nH 2O as cathode material for supercapacitors in Li 2SO 4, Na 2SO

4, and K 2SO 4 aqueous electrolytes. J. Power Sources 223, 56–61 (2013).

225. Liang, G. et al. A Universal Principle to Design Reversible Aqueous Batteries Based on

163

Deposition–Dissolution Mechanism. Adv. Energy Mater. 1901838, 1901838 (2019).

226. Grahame, D. C. Properties of the Electrical Double Layer at a Mercury Surface. I.

Methods of Measurement and Interpretation of Results. J. Am. Chem. Soc. 63, 1207–1215

(1941).

227. Ding, J., Hu, W., Paek, E. & Mitlin, D. Review of Hybrid Ion Capacitors: From Aqueous

to Lithium to Sodium. Chem. Rev. 118, 6457–6498 (2018).

228. Costentin, C. & Saveant, J.-M. Energy Storage: Pseudocapacitance in Prospect. Chem.

Sci. 5656–5666 (2019). doi:10.1039/c9sc01662g

229. Chen, Y., Shi, P. & Scherson, D. Supported iridium oxide films in aqueous electrolytes:

Charge injection dynamics as monitored by time-resolved differential reflectance

spectroscopy. Electrochem. Solid-State Lett. 11, (2008).

230. Giffin, G. A., Moretti, A., Jeong, S. & Passerini, S. Complex Nature of Ionic Coordination

in Magnesium Ionic Liquid-Based Electrolytes: Solvates with Mobile Mg 2+ Cations. J.

Phys. Chem. C 118, 39 (2014).

231. Costentin, C., Savéant, J.-M. & Savéant, S. Energy storage: pseudocapacitance in prospect

†. (2019). doi:10.1039/c9sc01662g

232. Costentin, C., Porter, T. R. & Savéant, J. M. Nature of Electronic Conduction in

‘pseudocapacitive’ Films: Transition from the Insulator State to Band-Conduction. ACS

Appl. Mater. Interfaces 11, 28769–28773 (2019).

233. Conway, B. E. Transition from ‘Supercapacitor’ to ‘Battery’ Behavior in Electrochemical

Energy Storage. J. Electrochem. Soc. 138, 1539–1548 (1991).

234. Conway, B. E. Two-dimensional and quasi-two-dimensional isotherms for Li intercalation

and upd processes at surfaces. Electrochim. Acta 38, 1249–1258 (1993).

164

235. Trasatti, S. & Petrii, O. Real surface area measurements in electrochemistry. Pure Appl.

Chem. 63, 711–734 (1991).

236. Chang, J.-K., Lee, M.-T. & Tsai, W.-T. In situ Mn K-edge X-ray absorption spectroscopic

studies of anodically deposited manganese oxide with relevance to supercapacitor

applications. J. Power Sources 166, 590–594 (2007).

237. Tanggarnjanavalukul, C., Phattharasupakun, N., Wutthiprom, J., Kidkhunthod, P. &

Sawangphruk, M. Charge storage mechanisms of birnessite-type MnO2 nanosheets in

Na2SO4 electrolytes with different pH values: In situ electrochemical X-ray absorption

spectroscopy investigation. Electrochim. Acta 273, 17–25 (2018).

238. Tanggarnjanavalukul, C., Phattharasupakun, N., Kongpatpanich, K. & Sawangphruk, M.

Charge storage performances and mechanisms of MnO2 nanospheres, nanorods,

nanotubes and nanosheets. Nanoscale 9, 13630–13639 (2017).

239. Black, J. M. et al. Strain-based in situ study of anion and cation insertion into porous

carbon electrodes with different pore sizes. Adv. Energy Mater. 4, 1–8 (2014).

240. Nakayama, M. et al. Cathodic Synthesis of Birnessite-Type Layered Manganese Oxides

for Electrocapacitive Catalysis. J. Electrochem. Soc. 159, A1176–A1182 (2012).

241. Systems, S. R. Operation and Service Manual QCM200 Quartz Crystal Microbalance

Digital Controller QCM25 5 MHz Crystal Oscillator. (2016).

242. Gabrielli, C., Keddam, M. & Torresi, R. Calibration of the Electrochemical Quartz Crystal

Microbalance. J. Electrochem. Soc. 138, 2657 (1991).

243. Peng, H. et al. Redox properties of birnessite from a defect perspective. Proc. Natl. Acad.

Sci. 114, 9523–9528 (2017).

244. Julien, C. et al. Raman spectra of birnessite manganese dioxides. Solid State Ionics 159,

165

345–356 (2003).

245. Zhitomirsky, I., Cheong, M. & Wei, J. The Cathodic Electrodeposition of Manganese

Oxide Films for Electrochemical Supercapacitors. JOM 59, 66–69 (2007).

246. Ma, N. et al. Effect of intercalated alkali ions in layered manganese oxide nanosheets as

neutral electrochemical capacitors. Chem. Commun. doi:2019/CC/C8CC08198K

247. Hsu, Y. K., Chen, Y. C., Lin, Y. G., Chen, L. C. & Chen, K. H. Reversible phase

transformation of MnO 2 nanosheets in an electrochemical capacitor investigated by in

situ Raman spectroscopy. Chem. Commun. 47, 1252–1254 (2011).

248. Shpigel, N. et al. In situ hydrodynamic spectroscopy for structure characterization of

porous energy storage electrodes. Nat. Mater. 15, 570–575 (2016).

249. Moreno, D. et al. In Situ Electrochemical Dilatometry of Phosphate Anion

Electrosorption. Environ. Sci. Technol. Lett. 5, 745–749 (2018).

250. Jäckel, N. et al. Electrochemical in Situ Tracking of Volumetric Changes in Two-

Dimensional Metal Carbides (MXenes) in Ionic Liquids. ACS Appl. Mater. Interfaces 8,

32089–32093 (2016).

251. Hantel, M. M. et al. In Situ Electrochemical Dilatometry of Onion-Like Carbon and

Carbon Black. J. Electrochem. Soc. 159, 1897–1903 (2012).

252. Arruda, T. M. et al. In situ tracking of the nanoscale expansion of porous carbon

electrodes. Energy Environ. Sci. 6, 225–231 (2013).

253. Ward, M. D. Principles and Applications of the Electrochemical Quartz Crystal

Microbalance. in Physical Electrochemistry: Principles, Methods, and Applications (ed.

Rubinstein, I.) 293–338 (MarcelDekker, Inc., 1995).

254. Chimola, J. et al. Anomalous Increase in Carbon Capacitance at Pore Sizes Less Than 1

166

Nanometer. Science (80-. ). 313, 1756–1760 (2006).

255. Wang, W., Juarez-Robles, D. & Mukherjee, P. P. Electroanalytical Quantification of

Electrolyte Transport Resistance in Porous Electrodes. J. Electrochem. Soc. 167, 080510

(2020).

256. Noked, M., Avraham, E., Soffer, A. & Aurbach, D. Assessing the concentration effect on

hydration radii in aqueous solutions by electroadsorption on a carbon molecular sieve

electrode. J. Phys. Chem. C 114, 13354–13361 (2010).

167

APPENDICES

168

Appendix A

Synthesis of Large Crystalline Birnessite Flakes

The initial goal of the birnessite project was to investigate the mechanical response of a single crystalline birnessite particle to electrochemical cycling. Our hypothesis was that by observing how the response varied from the edge to the center of the particle, we could understand the role that diffusion played in the apparent pseudocapacitance of birnessite. This required a synthesis which produced large crystals rather than the typical nanostructured material. We used the hydrothermal synthesis published by Xiong et al. in ACS Appl. Mater. Interfaces 2017, 9,

6282−6291. The procedure we followed is detailed below:

Birnessite Synthesis Plan

Dissolve 121.363 mg KMnO4 and 22.442 g KOH in 18.667 mL H2O, and then immediately add 1.333 mL of water with 96.64 mg of MnCl2 (for our reactor size. We cannot fill it more that

66%, a maximum of 29.7 mL). Stir until at room temperature, about two hours. Keep track of the time, be consistent across syntheses. Transfer solution to the Teflon-lined autoclave. Heat at 205

°C for 2 days (48 hours). After removing the hydrothermal reactor from the oven, place it in the fume hood and sit until cool, 2-3 hours. As described below, this time is also significant. Open in the fume hood so any released Cl2 gas goes to the scrubbers. Wash the product by adding DI water and separating it in the centrifuge until the solution is neutral pH. The particles are large, so ~2 minutes at 4500 RPM is fine.

169

Synthesis Results

While mixing the precursors, the initial solution changes color as the valence state of Mn varies. After hydrothermal synthesis, the supernatant solution should be a transparent dark turquoise color as in Figure 1, with a brown powder in the bottom of the reactor.

Figure 1. Color of solution after hydrothermal synthesis of birnessite. A) The dark turquoise Mn5+ solution in a centrifuge tube, and B) the same solution at a later step in the rinsing process, when it had been slightly diluted.

As shown by SEM in Figure 2, this synthesis produces nanobelts and approximately micron-sized platelets, with an ideal morphology for the intended birnessite studies.

170

Figure 2. SEM of the crystalline birnessite particles. Scale bar 1 μm.

The Raman spectra (Fig. 3) of these particles did show lots of peaks, which we initially attributed it to the crystallinity of the samples, as the XRD (Fig. 4) showed the expected birnessite structure. The “higher power” label in Figure 3 indicates the attenuator knob was slightly above the absolute minimum intensity at which I could get signal, while “lower power” was the lowest possible—this varies with time but is typically ~1.6 on the attenuator knob scale

171

Figure 3. Raman spectra of crystalline birnessite particles A) using a slightly higher power, which evolved a spinel component in the peak ~655, and B) a lower power which focused on the lower angle peaks. Both of these are significantly clearer than the Raman spectra discussed in Chapter 4, and show many peaks not commonly associated with birnessite.

Figure 4. XRD of the crystalline birnessite particles, which match PDF 00-042-1317.

172

To prepare simple electrode systems for the AFM studies, we sonicated the birnessite particles in water and dropcast thin films of particles directly onto glassy carbon. Kevin Matthews

(undergraduate researcher) determined that we could get decent adhesion (as measured by cycling stability) with ~ 60-100 μg/cm2 films heated at 60 °C after dropcasting from water. Figure 5 shows a CV at 5 mV/s in 1 M Na2SO4. This electrode had ~36-39 mAh/g capacity over a 1 V window, which is quite typical for birnessite.

0.03 GC 60C

0.02 )

-2 0.01

0.00

I (mA I cm (mA -0.01

-0.02

-0.03 0.0 0.2 0.4 0.6 0.8 1.0 Ewe (V vs Ag/AgCl)

Figure 5. Electrochemistry at 5 mV/s in 1 M Na2SO4 of birnessite dropcast onto glassy carbon

(GC) and heated at 60 °C. Kevin Matthews prepared this electrode and took this scan.

Figure 6 shows an AFM topography image taken in water using an Asylum MFP-3D AFM at NC State, which I was able to collect without the particles delaminating. This and the electrochemistry appeared quite promising for operando AFM dilatometry studies. However, we were unable to repeat the topography images at Oak Ridge National Lab (ORNL), as the AFM tips either got stuck in the film, or simply lifted the particles off the electrode. Dropcasting a film of

PVDF over the birnessite particles in an attempt to improve their adhesion only exacerbated the sticking problem.

173

Figure 6. AFM topography image of crystalline birnessite taken in water at NC State.

At this point, other projects in our lab had determined that electrodeposited electrodes were superior to dropcast films for the operando AFM studies. Therefore, we shifted the approach of the birnessite study to investigate the behavior of an electrodeposited film rather than a single particle. While no longer able to determine the mechanical response of a single particle, this study eventually became the fundamental study presented in Chapter 4.

This synthesis next came up while working on Chapter 3. In addition to comparing the behavior of the large expanded particles to activated carbon, it would be interesting to see if they do indeed provide higher volumetric capacitance than nanosized particles. However, when I went back to make the material, I was unable to reproduce the dull brown oxide described above. Each successive synthesis I tried resulted in a shiny and metallic-looking final product. This material was also stickier than before—the brown powder was pasty when damp and crumbled easily when

174

dried, where the shiny product was gummy when damp and formed hard rocky pellets upon drying.

While XRD showed the same pattern as Figure 4 above, the Raman continued to give unexpected peaks mentioned in Figure 3 above. Overall, I was not able to reproduce the brown powder birnessite material, although Kevin was. His solution was to carefully time each step, for ex:

1. Mix chemicals together, let stir for exactly 1 hour

2. Put solution in autoclave and heat at 205 °C for exactly 48 hours

3. Remove from oven and let cool for 2 hours (this was about the minimum time

required for the autoclave/hydrothermal reactor to cool down), then rinse

immediately.

Kevin eventually did SEM on some of this product and determined that the shininess was likely due to the large flakes he observed, which were several microns long. However, even when timing each step, I was unable to replicate the dull brown oxide. We moved on in our projects, rather than attempting to determine the reaction mechanisms within the hydrothermal reactor.

However, this study by Bor-Rong Chen et al. (Nature Communications, 2018, 9 DOI:

10.1038/s41467-018-04917-y) studies the crystallization pathways of manganese oxides during hydrothermal processes, and may be helpful if anyone attempts to recreate this process in the future.

175

Appendix B

Matlab Codes for Electrochemical, Dilatometry, and EQCM Data Analysis

Below are several matlab codes I put together with the help of Ruocun (John) Wang and

Naveen Pillai. I have included 4 here: CV stack, AFM single point code, EQCM analyzer, and

Mass-Charge-Ratio analyzer for birnessite.

B.1 CV Stacking Code

This code handles standard electrochemical cycling results. It can be run for several files at a time in the same folder. The input files are the default .mpt files exported from EC-lab. The sample mass should either be adjusted to the active mass of the electrode in grams, or 1 to avoid any normalization. Additionally, inputting the molecular weight and cation content allow for calculation of cation content at each point in the CV. This can be adjusted to only calculate charge passed, depending on which values are included in the calculations. The output of this code is CVs separated out by cycle and normalized by mass.

Title: CV_stack_v2.m

%version 2: added ability to analyze multiple files at once (using Ruocun (John) Wang's loops from the CV_analyzer, and made sure %the output data always included the input current %inputs: change the mass and number of cycles on lines 30 and 31 %if you want to use the Na+ (or cation in general) content, then change the %sample molar mass on line 32, and

%Load Files clearvars %% user inputs

%enter the appropriate values for your sample

176

mass = 0.00292; % mass of active material in g %cycles = 3; % Number of cycles Mol_Weight = 1; %Molar mass of NaNMCo (98.3026), NaNMFe (98.2245), NaNMCu (99.4543), NaMCu (102.3814), NaNMM (97.655), NaNM (104.531) i_Na = 0.0; %initial Na+ (or other cation, A+) content, experimental from ICP results

%% Find the sweep rates and number of headerlines in the allFiles = dir( '*.mpt' );% get the information all .mpt file in the current folder allNames = {allFiles(~[allFiles.isdir]).name};% get the names of the .mpt files Num_El = numel(allNames);% count the number of files in the folder for i = 1:1:Num_El% a for loop function to extract the number of headerlines and sweep rate from each .mpt file textFileName = char(allNames(i)); % convert the name of the i-th file into a string format readable by Matlab fileID = fopen(textFileName,'rt');% open the i-th file for getting headerline and sweep rate infos D = textscan(fileID,'%s','Delimiter','\n');% scan the text in the i-th file and save to D fclose(fileID);% close the file Headerlines_Num(i) = str2num(D{1}{2}(19))*10+str2num(D{1}{2}(20));% Find the number of headerlines in the 2nd row of D{1} which are stored in the 19th and 20th positions and convert the string format to a number format % find the sweep rate for sweep_rate_finder = 1:Headerlines_Num(i) Sweep_Rate_Line = D{1}{sweep_rate_finder}; Sweep_Rate_Key = 'dE/dt '; Sweep_Rate_Index = strfind(Sweep_Rate_Line, Sweep_Rate_Key); if Sweep_Rate_Index == 1 sweep_rate(i) = sscanf(Sweep_Rate_Line(Sweep_Rate_Index(1) + length(Sweep_Rate_Key):end), '%g', 1);% scan the line that stores the sweep rate data from the position that the Sweep_Rate_Key ends to where the line ends. The number is stored in the i-th position in the sweep_rate matrix. end end end

177

for i = 1:Num_El fileID = fopen(char(allNames(i)),'rt'); C = textscan(fileID, '%s','delimiter', '\n'); fclose(fileID); for ic = Headerlines_Num(i)+1:cellfun(@length,C) % start below the header j = ic-Headerlines_Num(i); % change the relative index so the new matrix doesn't have the headerlines A(j,:) = sscanf (char(C{1,1}(ic,1)),'%f'); D2(j,1,i) = A(j,6); %time D2(j,2,i) = A(j,8); % E_we D2(j,3,i) = A(j,9); % I (current) D2(j,4,i) = A(j,10);% Cycle number D2(j,5,i) = A(j,9)/mass; % Normalized current cycles(i) = max(D2(:,4,i)); end end

for rate_i = 1:Num_El%go through each file separately rows_thus_far = 0; cycle_length(1)= 0; k = 1; % Row Number Array = NaN(cellfun(@length,C),5,cycles(rate_i)); % Make an array with a separate sheet for each cycle %Na_Array = zeros(length(C),5,cycles*2); % Make an array with a separate sheet for each half cycle

for id = 1:cycles(rate_i) % loop through the sheets j=0; % Row Number rows_thus_far = rows_thus_far + cycle_length(id); while D2(k,4,rate_i) == id % while you are on cycle '#id'... j = j+1; %Move to the next if id >1 Array(k-rows_thus_far,:,id) = D2(k,:,rate_i); %Starting on the first line of the next page else Array(k,:,id) = D2(k,:,rate_i); %cc first page end

%Break condition for the while loop if k < length(A) %cellfun(@length,A) % (D is the raw data set) k = k+1;

178

else break end

cycle_length(id+1) = j; %Store number of data points in cycle '#id'

end end

Array2 = NaN(max(cycle_length),cycles(rate_i)*6); %make the array to print; changed to 6 for Na+ calc

for k = 1:cycles(rate_i) for i = 1:5 %changed from 5 to 6 for Na+ for j = 1:max(cycle_length(1+k)) Array2(j,6*k-6+i) = Array(j,i,k); end end end % k = 1;i=2;j=1; % Array2(j,i) = Array(j,i,k); %csvwrite(filename,Array2) %% Charge_passed = NaN(max(cycle_length),cycles(rate_i)); Na_content = NaN(max(cycle_length),cycles(rate_i));

for k=1:cycles(rate_i) Charge_passed(:,k) = (Mol_Weight/((6.022*10^23)*(1.6*10^- 19)*1000)).*cumtrapz(Array2(:,6*k-5),Array2(:,6*k-1)); if k == 1 Na_content(:,k) = i_Na-Charge_passed(:,1); else Na_content(:,k) = last_Na-Charge_passed(:,k); %why?? end last_Na = Na_content(length(find(~isnan(Na_content)))); %find the final content so values can cycle between things. Array2(:,6*k) = Na_content(:,k); % for j = 1:max(cycle_length(k)) % Charge_passed(:,k) = cumtrapz(Array2(:,6*k- 5),Array2(:,6*k-1),2); % Array2(j,6*k)=(3.6*Mol_Weight/((6.022*10^23)*(1.6*10^- 19))).*(Charge_passed(j,k)); % end end

179

%% Array3 = cell(max(cycle_length)+1,cycles(rate_i)*6);%added cols for Na+, changed s to 6s for k = 1:cycles(rate_i) %making headers for everything Array3(1,6*k-6+1:6*k-6+6) = {'time', 'Ewe', 'I', 'Cycle', 'I_g', 'A+ content'}; %changed 5s to 6s for Na+ added Na+ label end %Array3{2:end,:} = Array2 for k = 1:cycles(rate_i) for i = 1:6 %changed to 6 for A+ content for j = 1:max(cycle_length(1+k)) Array3{j+1,6*k-6+i} = Array2(j,6*k-6+i); %changed 5s to 6s; changed from Array(j,i,k) end end end % Convert cell to a table T = cell2table(Array3);

[fileloc,name_i,ext] = fileparts(char(allNames(rate_i))); xlswrite(name_i,Array3); end

B.2 AFM Single Point Analyzer

This code was written to anslye AFM dilatometry data taken at a single point. The input file should be a text file with columns for Ewe, I Analog 1 or 2 (whichever was used to record the dilatometry data in V), time, cycle number. This code takes single point AFM dilatometry data, subtracts a baseline, separates it into cycles, calculates the negative time derivative of the deformation, and exports both the individual cycle values, as well as the averages of all but the first and last cycles. Cycles are determined by cycle number, so setting scans to start and end at vertex potentials simplifies further data analysis.

Key variables are SGF, DF, and the conversion factor between deflection V and nm. The

SGF and DF determine how many points to apply the Savitsky-Golay Filter to at a time, while the

180

conversion factor must be calculated from a force-distance curve. The following figures go through the images plotted as the code runs.

First, check the plot of raw vs. filtered data to make sure the current SGF value does not over- or under-filter the data by either rounding out the data, or not removing any noise. This image is not currently saved as an output from the code. Figure 1 shows the baseline subtraction step, where the user must manually select the maxima of each cycle, which the code uses to find the local minima and fit a baseline to them. These images are from the 50 mV/s dilatometry of birnessite in K2SO4 described in Chapter 4.

Figure 1. Baseline to be subtracted from filtered deformation data.

Figure 2 shows the flattened deformation data (after baseline subtraction) as a function of time. Figure 3 shows the deformation data by cycle as a function of potential.

181

Figure 2. Baseline-subtracted deformation data (nm) vs. time (s).

Figure 3. Baseline-subtracted deformation data vs. potential. The legend shows the active material, sweep rate (in mV/s), and filter values—although DF has not yet been applied.

The negative time derivative of the deformation data correlates to the CV as shown by

Wang et al,208 allowing us to determine how electrochemical events connect to the local structural

182

response. This data requires the removal of outliners and subsequent filtering, as shown in Figure

4. The data can then be plotted vs. potential as in Figure 5.

Figure 4. The negative deformation rate as a function of time, showing the filtered data in the orange line. Filtering and outlier removal are important for removing sudden discontinuities from this noisy data.

Figure 5. Deformation rate and current vs. potential. This shows how the AFM data gives similar results to the current, which is discussed more in Chapter 4.

183

In addition to these images, two files are exported, one with averages of all but the first and last cycles, and one with data from each of these single cycles.

Title: AFM_SinglePoint_SB_v8.m

%%Version 8: changed baseline to use 'makima' %%Version 7: added outlier replacement with value of previous data. The %%goal is to reduce enough of the outliers that they don't appear in the %%filtered dataset. Also improved filtering of the deformation rate data. %Updated 12/18/2019 %Authors: Shelby Boyd (the actual code), Naveen Pillai (file importing), Ruocun (John) %Wang (code flow process/starting code version that Shelby completely rewrote) %% Instructions % 1) Input file: export a .txt or .mpt file with no headerlines and columns in % this order: Ewe, I Analog 1 or 2*, time, cycle number % *whichever you used to collect the deformation data % 2) In the User Inputs section (line 59), enter: % anodic and cathodic turnover potentials % tip conversion factor (nm/v) % Window length for filtering, SGF % Material molecular weight, and initial cation content % Choose the filter order, line 69 column 35. % Some troubleshooting tips are included at the bottom of the file % Assumptions % background was assumed to be a spline between the lowest % deformation values in each CV cycles. %% Code structure % load file % background subtraction % deformation rate calculation % data visualization %% Load file

% Get the Matrix clear all close all %close all open figure windows

184

getFile = dir( '*.txt' );% get the one file (technically, all files) if size(getFile,1) == 0 %check to see if you got a file fprintf('No files of specified type in this folder') %warn user if not end

FileName = char({getFile(~[getFile.isdir]).name}); %get the name C = textread(FileName, '%s','delimiter', '\n'); %recieve the file linestart = 5; %where the data starts, will vary depending on EC lab file export format %change the size of the imported matrix to reflect # of columns in .mpt %file Imported_Matrix=zeros(length(C)- linestart,5,length(getFile));%want it to be full of data so there aren't random zeros messing things up Sample_Info = inputdlg({'Sample Name','Sweep Rate in mV/s', 'Material',}); name = num2str(Sample_Info{1}); rate = num2str(Sample_Info{2}); material = num2str(Sample_Info{3}); for ic = linestart:length(C) Imported_Matrix(ic-linestart+1,:) = str2num(string(C{ic})); %chuck all the good stuff into a giant matrix end

% Put the imported data into a matrix with extra columns for baseline % subtraction and taking the derivative CC(:,1) = Imported_Matrix(:,1); % "Ewe/V" CC(:,2) = Imported_Matrix(:,2); % "/mA" CC(:,3) = Imported_Matrix(:,3); % "Analog IN 2/V" 13 used for June 2019 trip. This might be column 12 depending on which setting you used at ORNL CC(:,5) = Imported_Matrix(:,4); % "time/s" CC(:,7) = Imported_Matrix(:,5); % "cycle number"

%% User Inputs Anod_V = 0.9; %anodic (most positive) turnover potential Cath_V = -0.1; %cathodic (least positive) turnover potential ConF = 105.76; %conversion factor SGF = 125; %SG filter framelength (number of points to smooth over). Must be an odd number. WO3 used 251.

185

DF = 51; %SGF framelength for the derivative Mol_Mass = 98.2; %molecular mass of your material, if you want to calculate incremental capacity Sample_mass = .000055858; i_A = 0.15; %initial cation content of your material, if you want to calculate incremental capacity

%% Remove outliers and filter raw deformation data time = CC(:,5); def = CC(:,3);%deformation no_def = filloutliers(def,'previous','movmean',1000); %find outliers more than 3 standard deviations from the mean within a 1000 point window, and replace them with the previous value in the data column no_def = filloutliers(no_def,'previous','movmean',100); %repeat but with a 100 point window filt_deform = sgolayfilt(no_def, 2, SGF);% Savitzky_Golay filtering on the deformation data SKB june order 2 CC(:,3) = filt_deform;%replace the raw data with the filtered data figure(1); %plot the initial data vs. the filtered data plot(time,def,time,no_def,time,filt_deform) xlabel('time (s)') ylabel('deformation') legend('raw data','filtered deformation','deformation') saveas(gcf,'baseline.png')%save the current figure

%% Get the indexes where each CV cycle starts [but this is actually the index for where it ends and I do not understand why] cycles=max(CC(:,7)); Cycle_Change = zeros(1,cycles); cycle_count = 1; for j = 1:length(CC)-1 if CC(j,7) < CC(j+1,7) Cycle_Change(cycle_count) = j+1; cycle_count = cycle_count +1; end end

Cycle_Change(max(CC(:,7))) = size(CC,1); %% Background subtraction %this baseline will not use the first and last cycle % Find peaks (in deformation) in order to determine valleys for i=1:cycles

186

time_cc(i)=time(Cycle_Change(i));%store the time indices of the cycle changes end figure(2)%plot the filtered data, peaks, minima, and baseline. %B = filloutliers(filt_deform,'nearest','mean'); %Afill = filloutliers(filt_deform,'next'); %B = filloutliers(filt_deform,'clip'); plot(time,filt_deform); title('Select peak maxima, starting after the 1st minimim. Only click once per cycle'); xlabel('time (s)') ylabel('deformation (V)') [peak_time,peak_def]=ginput(cycles);

% PP=0.015;%peak prominence factor % figure(2)%plot the filtered data, peaks, minima, and baseline. % findpeaks(filt_deform,time,'MinPeakProminence',PP); %opens a plot with the filtered deformation and the peaks % %check that the peaks are showing up in the right place. May have to adjust the sensitivity factor % [peak_def,peak_time]=findpeaks(filt_deform,time,'MinPeakProminen ce',PP);%store the maximum deformation values in peak_def, and the time in peak_time row = zeros(cycles,1); for i = 1:cycles%store the index of each maximum [temp row(i)] = min(abs(time-peak_time(i)));%temp is the minimum distance between a selected time point and the nearest actual time % [row(i)]=find(r_time==peak_time(i)); end %use the peak locations to find the minima in the filtered signal, and the %corresponding time, displacement, and location for each cycle for i = 1:cycles if i == 1 min_deform(1)=min(filt_deform(1:row(i))); min_indices(i)=find(filt_deform==min_deform(i));%find the index of each minimum min_time(i)=time(min_indices(i));%find the time of each minimum min_ewe(i)=CC((min_indices(i)),1);%find the potential of each minimum else

187

min_deform(i)=min(filt_deform(row(i-1):row(i)));%find the minimum deformation of each cycle min_indices(i)=find(filt_deform==min_deform(i));%find the index of each minimum min_time(i)=time(min_indices(i));%find the time of each minimum min_ewe(i)=CC((min_indices(i)),1);%find the potential of each minimum end end

% for i = 1:cycles %for the baseline for all cycles % min_deform(i)=min(filt_deform(1:row(i)));%find the minimum deformation of each cycle % min_indices(i)=find(filt_deform==min_deform(i));%find the index of each minimum % min_time(i)=time(min_indices(i));%find the time of each minimum % min_ewe(i)=CC((min_indices(i)),1);%find the potential of each minimum % end hold on scatter(time_cc,peak_def)%show where the cycle changes. The deformation value just uses the peak value because it's easy hold on scatter(min_time,min_deform)%plot the minima dx=time(min_indices(1):min_indices(cycles));%the number of points over which to calculate a baseline baseline=makima(min_time,min_deform,dx); %makima avoids overshoots better than spline. Use spline for versions before R2019a hold on plot(time(min_indices(1):min_indices(cycles)),baseline)%figure 2 should now have the filtered signal, the maxima, minima, and baseline between all cycles except for the first and last legend('filtered deformation','max. deformation','min. deformation','baseline','cycle change') saveas(gcf,'baseline.png')%save the current figure bs_def = NaN(length(CC),1); %subtract the baseline from the filtered data for i = min_indices(1):min_indices(cycles) bs_def(i)=CC(i,3)-baseline(i-min_indices(1)+1); end

188

CC_short=zeros(Cycle_Change(cycles-1)-Cycle_Change(1),7);%put the original data into a new matrix so we can subtract the baseline from the filtered deformation for j=1:7 %cut out the first and last cycles using the indices of the minima CC_short(:,j)=CC(Cycle_Change(1):Cycle_Change(cycles-1)- 1,j); %1=Ewe, 2=I (mA), 3=deformation, 5=time (s), 7=cycle number end for i=1:length(CC_short) %subtract the baseline and store it in column 4 of CC_short CC_short(i,4)=bs_def(i+Cycle_Change(1))*ConF; %column 4 is now baseline-subtracted deformation in nanometers end figure(3) %plot the filtered data after baseline subtraction plot(CC_short(:,5),CC_short(:,4),CC_short(:,5),CC_short(:,1)) xlabel('time (s)') ylabel('deformation (nm)') legend('filtered deformation-baseline') saveas(gcf,'Flat Filt Def.png')%save the current figure

%% d(Deformation)/dt dDeformdx_tot = diff([eps; CC_short(:,4)])./diff([eps; CC_short(:,5)]);%differendiate the deformation data wrt time (nm/s) no_dDef=filloutliers(dDeformdx_tot,'previous','movmean',1000); %find outliers more than 3 standard deviations from the mean within a 1000 point window, and replace them with the previous value in the derivative column no_dDef=filloutliers(no_dDef,'previous','movmean',100); %repeat but with a 100 point window filt_dDeformdx_tot = sgolayfilt(no_dDef, 3, DF); CC_short(:,6)=filt_dDeformdx_tot*-1; %store the negative derivative of the deformation data in CC_short with the rest of the data. Yay! Now it's all in one place. figure(4) %plot the derivative and the filtered derivative to make sure they fit together. plot(CC_short(:,5),CC_short(:,4)) saveas(gcf,'Flat Filt Def.png')%save the current figure plot(CC_short(:,5),no_dDef,CC_short(:,5),filt_dDeformdx_tot) xlabel('time (s)') ylabel('-deformation rate (-nm/s)') legend('deformation rate','filtered deformation rate') saveas(gcf,'Def Rate.png')%save the current figure %put each cycle on its own sheet

189

k = 1; %row number to use for indexing arrays all_data=NaN(Cycle_Change(2)-Cycle_Change(1),8,cycles-2);%make a matrix for all but the first and last, with the baseline- subtracted data, with each cycle on its own separate sheet. rows_thus_far = 0; cycle_length(1) = 0; i=2; for i=2:cycle_count %loop through the sheets to put each cycle on its own sheet. j = 0; %row number for the loop rows_thus_far = rows_thus_far + cycle_length(i-1); while CC_short(k,7) == i %while on cycle #i j = j+1; %move to the next row if i >2 %because we're starting with 2, since the first cycle is already subtracted from the data all_data(k-rows_thus_far,1:7,i-1) = CC_short(k,:); %Skip the current page and start on the first line of the next page else all_data(k,1:7,i-1) = CC_short(k,:); %put the 2nd cycle data on the first page end %break the while loop if k < length(CC_short) k = k+1; else break end cycle_length(i) = j; %store the number of data points from cycle #i end end

%% Calculate the cation content Charge_passed = NaN(length(all_data),cycles); A_content = NaN(length(all_data),cycles);

for k=1:cycles-2 Charge_passed(:,k) = (Mol_Mass/(Sample_mass*(6.022*10^23)*(1.6*10^- 19)*1000)).*cumtrapz(all_data(:,5,k),all_data(:,2,k)); if k == 1 A_content(:,k) = i_A-Charge_passed(:,1); else A_content(:,k) = last_A-Charge_passed(:,k); %why?? end

190

last_A = A_content(length(find(~isnan(A_content)))); %find the final content so values can cycle between things. all_data(:,8*k) = A_content(:,k); end

%% Data visualization % plot Def vs. E and I vs. E / Def vs. time fig = figure(5); linecolors = jet(cycle_count); left_color = [0 0 0]; right_color = [0 0 0]; set(fig,'defaultAxesColorOrder',[left_color; right_color]); for sheet= 1:cycles-2 %use this to determine how many cycles you want to show plot(all_data(:,1,sheet), all_data(:,4,sheet),'- ','color',linecolors(sheet,:),'linewidth',2) hold on end xlabel('Ewe (V {\itvs.} Ag/AgCl)')%change for the relevant reference electrode used ylabel('Deformation (nm)') h = legend(sprintf('%s %s, SGF %d, DF %d', material, rate, SGF, DF)); LEG = findobj(h,'type','text'); hold off %baseline_in_nm = baseline*SenF; hL = zeros(cycle_count,1); saveas(gcf,'Def vs Ewe.png')

% plot derivative of Def fig2 = figure(11); set(fig2,'defaultAxesColorOrder',[linecolors(2,:); linecolors(cycles-3,:)]); [min_k, p] = min(abs(k)); yyaxis left for sheet= 1:cycles-2 %use this to determine how many cycles you want to show plot(all_data(:,1,sheet), all_data(:,6,sheet),'- ','color',linecolors(2,:),'linewidth',2) hold on end ylabel('-d(Deformation)/dt (nm/sec)') hold on yyaxis right for sheet= 1:cycles-2 %use this to determine how many cycles you want to show

191

plot(all_data(:,1,sheet), all_data(:,2,sheet),'- ','color',linecolors(cycles-3,:),'linewidth',2) hold on end ylabel('Current (mA)') xlim([Cath_V Anod_V]) hold off xlabel('Potential (V {\itvs.} Ag/AgCl)')%change for the relevant reference electrode used h = legend(sprintf('%s %s mV/s, SGF %d, DF %d', material, rate, SGF, DF)); LEG = findobj(h,'type','text'); set(LEG,'FontSize',20) saveas(gcf,'Def I CVs.png')

% % Find integration at each time for the pth cycle % It_neg = [t(I(:,p)<0,p),I(I(:,p)<0,p)];% Get time and current that is less than 0 % t_neg = t(I(:,p)<0,p)-min(t(I(:,p)<0,p)); % It_pos = [t(I(:,p)>=0,p),I(I(:,p)>=0,p)];% Get time and current that is greater than or equal to 0 % t_pos = t(I(:,p)>=0,p)-min(t(I(:,p)>=0,p)); % Cath_Cap = NaN(size(It_neg,1),1); % Anod_Cap = NaN(size(It_pos,1),1); % for pos_count = 2:size(It_pos,1) % Anod_Cap(pos_count) = abs(trapz(It_pos(1:pos_count,1), It_pos(1:pos_count,2)));% integration to find anodic capacity % end % for neg_count = 2:size(It_neg,1) % Cath_Cap(neg_count) = abs(trapz(It_neg(1:neg_count,1), It_neg(1:neg_count,2)));% integration to find anodic capacity % end % figure (12) % plot(t_pos,(8-Anod_Cap)*4) % hold on % plot(t_pos,deform_nobase(I(:,p)>=0,p)*2546) % hold off %% Average the cycles % want average deformation, I, and deformation rate, all wrt potential all_avg=NaN(length(all_data),9);%same length, with Ewe, I, def, ddef/dt, A+ content and 4 sets of standard deviations all_avg(:,1)=all_data(:,1,2); for j=1:4 for i = 1:length(all_data) all_avg(i,2*j)=sum(all_data(i,2*j,2:cycles-2), 'omitnan')/(all_data(1,7,cycles-2)-all_data(1,7,2));%average

192

each value by the number of cycles included in the analysis (total-2) all_avg(i,1+2*j)=std(all_data(i,2*j,:), 'omitnan');%add the standard deviation of each value in the following column end end %% Export the data Avg_Array=cell(length(all_avg)+1,9); Avg_Array(1,:)= {'Ewe', 'I', 'Standard Deviation of I', 'Deformation (nm)', 'Standard Deviation of Def (nm)', '- deformation rate (nm/s)', 'Standard Deviation of -ddef/dt (nm/s)', 'Average A+ Content', 'Standard Deviation of A+ Content'}; for j = 2:length(Avg_Array)%for each row for i=1:9 Avg_Array{j,i}=all_avg(j-1,i); end end Array3 = cell(length(all_data)+1,(cycle_count-2)*8);%make a giant array with room to put all of the sheets of all_data onto a single page for k = 1:cycle_count-2 %making headers for everything Array3(1,8*k-8+1:8*k-8+8) = {'Ewe', 'I', 'Deformation', 'Baseline-subtracted Deformation (nm)', 'time', '-deformation rate (nm/s)', 'Cycle', 'A+ Content'}; end for k = 1:cycles-2 %for each "sheet", but remember we have one less sheet than number of cycles for i = 1:8 %each column for j = 1:max(cycle_length(k+1))%each row Array3{j+1,8*k-8+i} = all_data(j,i,k); %stack all the sheets of "all_data" next to each other end end end filename = strcat(name,'_',rate); avg_name = strcat(filename,'_averages'); xlswrite(filename, Array3); %change sample name xlswrite(avg_name, Avg_Array); %writecell(Array3,'100mvps.xlsx'); for when xlswrite stops working

%Troubleshooting: % line 99: left and right sides not matching.

193

% 1) check that the values for peak_time (maxima time points) are all within the bounds of % r_time (rounded time). If a value in peak_time is outside (past) the values of % r_time, start over and be careful that the filtered data appears % in the crosshairs when selecting peak maxima. % 2) check that there is only one of each time value in r_time. If % there are multiples, increase the number of decimals used to % round the peak time and time (lines 102 and 103, or thereabouts. % Look for the 'round' function

B.3 EQCM Analyzer

This code is a modification of the AFM code to handle EQCM data. The main changes are that an endpoint must be selected for baseline subtraction, and the first and last cycles are no longer deleted. Figure 6 shows the difference in baseline subtraction, although all other figures are the same.

Figure 6. Baseline subtraction in the EQCM code.

194

Title: EQCM_analyzer_v2.m

%%EQCM version of the AFM code based on AFM_SinglePoint_SB_v8 %Updated 05/21/2020 to take the negative derivative %Authors: Shelby Boyd (the actual code), Naveen Pillai (file importing), Ruocun (John) %Wang (code flow process/starting code version that Shelby completely rewrote) %% Instructions % 1) Input file: export a .txt or .mpt file with no headerlines and columns in % this order: Ewe, I Analog 1 or 2*, time, cycle number % *whichever you used to collect the deformation data % 2) In the User Inputs section (line 59), enter: % anodic and cathodic turnover potentials % tip conversion factor (nm/v) % Window length for filtering, SGF % Material molecular weight, and initial cation content % Choose the filter order, line 69 column 35. % Some troubleshooting tips are included at the bottom of the file % Assumptions % background was assumed to be a spline between the lowest % deformation values in each CV cycles. %if you don't want to filter your data, then comment out lines 76 and 77 %(should just have eqcm=CC(:,3) %% Code structure % load file % background subtraction % deformation rate calculation % data visualization %% Load file

% Get the Matrix clear all close all %close all open figure windows getFile = dir( '*.txt' );% get the one file (technically, all files) if size(getFile,1) == 0 %check to see if you got a file fprintf('No files of specified type in this folder') %warn user if not end

FileName = char({getFile(~[getFile.isdir]).name}); %get the name

195

C = textread(FileName, '%s','delimiter', '\n'); %recieve the file linestart = 3; %where the data starts, will vary depending on EC lab file export format %change the size of the imported matrix to reflect # of columns in .mpt %file Imported_Matrix=zeros(length(C)- linestart,5,length(getFile));%want it to be full of data so there aren't random zeros messing things up Sample_Info = inputdlg({'Sample Name','Sweep Rate in mV/s', 'Material',}); name = num2str(Sample_Info{1}); rate = num2str(Sample_Info{2}); material = num2str(Sample_Info{3}); for ic = linestart:length(C) Imported_Matrix(ic-linestart+1,:) = str2num(string(C{ic})); %chuck all the good stuff into a giant matrix end

%% User Inputs Anod_V = 0.9; %anodic (most positive) turnover potential Cath_V = -0.1; %cathodic (least positive) turnover potential %ConF = 68.4; %conversion factor SGF =25; %SG filter framelength (number of points to smooth over). Must be an odd number. WO3 used 251. DF = 51; %SGF framelength for the derivative Mol_Mass = 98.2; %molecular mass of your material, if you want to calculate incremental capacity Sample_mass = 1; i_A = 0; %it's effectively the initial number of e- passed Cf = -0.02442;% ug/Hz

%% Remove outliers and filter raw deformation data time = CC(:,5);

196

no_eqcm = CC(:,3);%deformation no_eqcm = filloutliers(no_eqcm,'previous','movmean',1000); %find outliers more than 3 standard deviations from the mean within a 1000 point window, and replace them with the previous value in the data column no_eqcm = filloutliers(no_eqcm,'previous','movmean',100); %repeat but with a 100 point window CC(:,3) = sgolayfilt(no_eqcm, 2, SGF);% Savitzky_Golay filtering on the deformation data SKB june order 2 eqcm = CC(:,3)% = filt_deform;%replace the raw data with the filtered data figure(1); %plot the initial data vs. the filtered data plot(time,no_eqcm,time,eqcm)%,time,filt_deform) xlabel('time (s)') ylabel('frequency change') legend('raw data','outliers removed')%,'deformation') saveas(gcf,'baseline.png')%save the current figure

Cycle_Change(max(CC(:,7))) = size(CC,1); %% Background subtraction %changing it to include first and last cycle % Find peaks (in deformation) in order to determine valleys for i=1:cycles time_cc(i)=time(Cycle_Change(i));%store the time indices of the cycle changes end figure(2)%plot the filtered data, peaks, minima, and baseline. plot(time,eqcm); title('Select peak maxima starting after the 1st minimim, and the last data point.'); xlabel('time (s)')

197

ylabel('frequency (hz)') [peak_time,peak_def]=ginput(cycles+1); row = zeros(cycles+1,1); for i = 1:cycles+1%store the index of each maximum [temp row(i)] = min(abs(time-peak_time(i)));%temp is the minimum distance between a selected time point and the nearest actual time % [row(i)]=find(r_time==peak_time(i)); end %use the peak locations to find the minima in the filtered signal, and the %corresponding time, displacement, and location for each cycle for i = 1:cycles+1 if i == 1 min_deform(1)=min(eqcm(1:row(i))); min_indices(i)=find(eqcm==min_deform(i));%find the index of each minimum min_time(i)=time(min_indices(i));%find the time of each minimum min_ewe(i)=CC((min_indices(i)),1);%find the potential of each minimum else min_deform(i)=min(eqcm(row(i-1):row(i)));%find the minimum deformation of each cycle min_indices(i)=find(eqcm==min_deform(i));%find the index of each minimum min_time(i)=time(min_indices(i));%find the time of each minimum min_ewe(i)=CC((min_indices(i)),1);%find the potential of each minimum end end hold on scatter(peak_time,peak_def)%show where the cycle changes. The deformation value just uses the peak value because it's easy hold on scatter(min_time,min_deform)%plot the minima dx=time(min_indices(1):min_indices(cycles+1));%the number of points over which to calculate a baseline baseline=makima(min_time,min_deform,dx); %makima avoids overshoots better than spline. Use spline for versions before R2019a hold on

198

plot(time(min_indices(1):min_indices(cycles+1)),baseline)%figure 2 should now have the filtered signal, the maxima, minima, and baseline between all cycles except for the first and last legend('frequency change','max. change','min. change','baseline','cycle change') saveas(gcf,'baseline.png')%save the current figure bs_def = NaN(length(CC),1); %subtract the baseline from the filtered data for i = min_indices(1):min_indices(cycles+1) bs_def(i)=CC(i,3)-baseline(i-min_indices(1)+1); end

% CC_short=zeros(Cycle_Change(cycles-1)-Cycle_Change(1),7);%put the original data into a new matrix so we can subtract the baseline from the filtered deformation % for j=1:7 %cut out the first and last cycles using the indices of the minima % CC_short(:,j)=CC(Cycle_Change(1):Cycle_Change(cycles-1)- 1,j); %1=Ewe, 2=I (mA), 3=deformation, 5=time (s), 7=cycle number % end for i=1:length(CC) %subtract the baseline and store it in column 4 of CC_short CC(i,4)=Cf*bs_def(i);%*ConF; %column 4 is now baseline- subtracted deformation in nanometers end CC = CC(min_indices(1):min_indices(cycles+1),:); figure(3) %plot the filtered data after baseline subtraction plot(CC(:,5),CC(:,4),CC(:,5),CC(:,1)) xlabel('time (s)') ylabel('mass change (ug)') legend('baseline-subtracted deltaM') saveas(gcf,'Flat Delta M.png')%save the current figure

%% d(Deformation)/dt dDeformdx_tot = diff([eps; CC(:,4)])./diff([eps; CC(:,5)]);%differendiate the deformation data wrt time (nm/s) no_dDef=filloutliers(dDeformdx_tot,'previous','movmean',1000); %find outliers more than 3 standard deviations from the mean within a 1000 point window, and replace them with the previous value in the derivative column no_dDef=filloutliers(no_dDef,'previous','movmean',100); %repeat but with a 100 point window no_dDef=filloutliers(no_dDef,'previous','movmean',50);

199

filt_dDeformdx_tot = sgolayfilt(no_dDef, 3, DF); CC(:,6)=(-1)*filt_dDeformdx_tot; %storing the derivative of the frequency change data in CC_short with the rest of the data. Yay! Now it's all in one place. figure(4) %plot the derivative and the filtered derivative to make sure they fit together. plot(CC(:,5),CC(:,4)) saveas(gcf,'Flat Filt Def.png')%save the current figure plot(CC(:,5),no_dDef,CC(:,5),filt_dDeformdx_tot) xlabel('time (s)') ylabel('delta M/dt (ug/s)') legend('mass change rate','filt. mass change rate') saveas(gcf,'mass Rate.png')%save the current figure

%put each cycle on its own sheet k = 1; %row number to use for indexing arrays all_data=NaN(Cycle_Change(2)-Cycle_Change(1),8,cycles);%make a matrix for all, with the baseline-subtracted data, with each cycle on its own separate sheet. rows_thus_far = 0; cycle_length(1) = 0; i=2; for i=2:cycles+1 %loop through the sheets to put each cycle on its own sheet. j = 0; %row number for the loop rows_thus_far = rows_thus_far + cycle_length(i-1); while CC(k,7) == i-1 %while on cycle #i j = j+1; %move to the next row % if i >2 %because we're starting with 2, since the first cycle is already subtracted from the data % all_data(k-rows_thus_far,1:7,i-1) = CC(k,:); %Skip the current page and start on the first line of the next page % else all_data(k-rows_thus_far,1:7,i-1) = CC(k,:); %put the 2nd cycle data on the first page % end %break the while loop if k < length(CC) k = k+1; else break end cycle_length(i) = j; %store the number of data points from cycle #i end end

200

%% Calculate the charge passed Charge_passed = NaN(length(all_data),cycles); A_content = NaN(length(all_data),cycles);

for k=1:cycles Charge_passed(:,k) = (0.001).*cumtrapz(all_data(:,5,k),all_data(:,2,k)); % if k == 1 % A_content(:,k) = i_A-Charge_passed(:,1); % else % A_content(:,k) = last_A-Charge_passed(:,k); %why?? % end % last_A = A_content(length(find(~isnan(A_content)))); %find the final content so values can cycle between things. all_data(:,8*k) = Charge_passed(:,k); end

%% Data visualization % plot Def vs. E and I vs. E / Def vs. time fig = figure(5); linecolors = jet(cycle_count); left_color = [0 0 0]; right_color = [0 0 0]; set(fig,'defaultAxesColorOrder',[left_color; right_color]); for sheet= 1:cycles-2 %use this to determine how many cycles you want to show plot(all_data(:,1,sheet), all_data(:,4,sheet),'- ','color',linecolors(sheet,:),'linewidth',2) hold on end xlabel('Ewe (V {\itvs.} Ag/AgCl)')%change for the relevant reference electrode used ylabel('delta M (ug)') h = legend(sprintf('%s %s, SGF %d, DF %d', material, rate, SGF, DF)); LEG = findobj(h,'type','text'); hold off %baseline_in_nm = baseline*SenF; hL = zeros(cycle_count,1); saveas(gcf,'delM vs Ewe.png')

% plot derivative of mass change fig2 = figure(11); set(fig2,'defaultAxesColorOrder',[linecolors(2,:); linecolors(cycles,:)]); [min_k, p] = min(abs(k));

201

yyaxis left for sheet= 1:cycles %use this to determine how many cycles you want to show plot(all_data(:,1,sheet), all_data(:,6,sheet),'- ','color',linecolors(2,:),'linewidth',2) hold on end ylabel('-ddelta M/dt (ug/s)') hold on yyaxis right for sheet= 1:cycles %use this to determine how many cycles you want to show plot(all_data(:,1,sheet), all_data(:,2,sheet),'- ','color',linecolors(cycles,:),'linewidth',2) hold on end ylabel('Current (mA)') xlim([Cath_V Anod_V]) hold off xlabel('Potential (V {\itvs.} Ag/AgCl)')%change for the relevant reference electrode used h = legend(sprintf('%s %s mV/s, SGF %d, DF %d', material, rate, SGF, DF)); LEG = findobj(h,'type','text'); set(LEG,'FontSize',20) saveas(gcf,'delM I CVs.png')

%% Average the cycles % want average deformation, I, and deformation rate, all wrt potential all_avg=NaN(length(all_data),9);%same length, with Ewe, I, def, ddef/dt, A+ content and 4 sets of standard deviations all_avg(:,1)=all_data(:,1,2); for j=1:4 for i = 1:length(all_data) all_avg(i,2*j)=sum(all_data(i,2*j,2:cycles), 'omitnan')/(all_data(1,7,cycles)-all_data(1,7,2));%average each value by the number of cycles included in the analysis (total-2) all_avg(i,1+2*j)=std(all_data(i,2*j,:), 'omitnan');%add the standard deviation of each value in the following column end end %% Export the data Avg_Array=cell(length(all_avg)+1,9); Avg_Array(1,:)= {'Ewe', 'I', 'Standard Deviation of I', 'delta M (ug)', 'Standard Deviation of delta M Hz)', '-deltaM rate

202

(ug/s)', 'Standard Deviation of -dM/dt (ug/hz)', 'e- passed', 'Standard Deviation of e- passed'}; for j = 2:length(Avg_Array)%for each row for i=1:9 Avg_Array{j,i}=all_avg(j-1,i); end end Array3 = cell(length(all_data)+1,(cycle_count)*8);%make a giant array with room to put all of the sheets of all_data onto a single page for k = 1:cycle_count %making headers for everything Array3(1,8*k-8+1:8*k-8+8) = {'Ewe', 'I', 'Frequency Change', 'delta M (ug)', 'time', '-deltaM rate (ug/s)', 'Cycle', 'mol e- passed'}; end for k = 1:cycles %for each "sheet", but remember we have one less sheet than number of cycles for i = 1:8 %each column for j = 1:max(cycle_length(k+1))%each row Array3{j+1,8*k-8+i} = all_data(j,i,k); %stack all the sheets of "all_data" next to each other end end end filename = strcat(name,'_',rate); avg_name = strcat(filename,'_averages'); xlswrite(filename, Array3); %change sample name xlswrite(avg_name, Avg_Array); %writecell(Array3,'100mvps.xlsx'); for when xlswrite stops working

%Troubleshooting: % line 99: left and right sides not matching. % 1) check that the values for peak_time (maxima time points) are all within the bounds of % r_time (rounded time). If a value in peak_time is outside (past) the values of % r_time, start over and be careful that the filtered data appears % in the crosshairs when selecting peak maxima. % 2) check that there is only one of each time value in r_time. If % there are multiples, increase the number of decimals used to

203

% round the peak time and time (lines 102 and 103, or thereabouts. % Look for the 'round' function

B.4 QCM solver code

Because EQCM data only shows the net mass change of an electrode during cycling, it cannot differentiate the exact reaction mechanisms that may be taking place. This code was written to illustrate the variety of potential reactions for each mass-charge ratio measured in birnessite in

K2SO4. Figure 7 shows the potential reaction mechanisms and equations I considered based on the species present in the electrolyte. Here, a and b are coefficients calculated by the code.

Figure 7. Various potential equations for two-species redox reactions occurring in birnessite

MnO2 upon electrochemistry in a K2SO4 electrolyte.

204

To do this, I made input text files in the format of Table I. The MCR went in the first column, with the change in charge (delta Q) in the second column. The code uses the delta Q to determine whether the MCR was calculated during the anodic or cathodic sweep. Ci and Cf are the initial and final amounts of charge, respectively, in Coulombs.

Table I. Inputs for QCM Solver MCR delta Q Ci Cf 29.1857 0.017954 5.56E-05 0.01801 16.754 0.00773 0.01839 0.02612 24.3795 -0.02527 0.02636 0.00109

Figure 8 shows one example of the results for an anodic MCR. Each color line represents a different possible equation, and a and b are the values of the first and second species in the legend, respectively.

Figure 8. Example results of the EQCM film discussed in Chapter 4 at 5 mV/s, for an MCR of

29.2 g/mol e-.

205

+ + + - + - + This figure shows six different possible equations: K -H2O, H -H2O, K -OH , H -OH , K -

2- + 2- SO4 , H -SO4 . We decided to go with the simplest explanation in Chapter 4, which thus far appear to be verified by our computational collaborators. However, the goal of this code was to demonstrate that multiple results are mathematically possible, and additional experimental methods must be used to determine the actual mechanisms taking place during electrochemistry.

Title: QCM_solver_v2.m % QCM solver that takes your Mass Charge Ratios (MCR) and solves for % two-component equations. clear close all %% Load file

FileName = char({getFile(~[getFile.isdir]).name}); %get the name C = textread(FileName, '%s','delimiter', '\n'); %recieve the file linestart = 2; %where the data starts, will vary depending on EC lab file export format %change the size of the imported matrix to reflect # of columns in .mpt %file Imported_Matrix=zeros(length(C)- linestart,4,length(getFile));%want it to be full of data so there aren't random zeros messing things up % Sample_Info = inputdlg({'Sample Name','Sweep Rate in mV/s', 'Material',}); % name = num2str(Sample_Info{1}); % rate = num2str(Sample_Info{2}); % material = num2str(Sample_Info{3});

206

for ic = linestart:length(C) Imported_Matrix(ic-linestart+1,:) = str2num(string(C{ic})); %chuck all the good stuff into a giant matrix end

% Put the imported data into a matrix with extra columns for baseline % subtraction and taking the derivative CC(:,1) = Imported_Matrix(:,1); % MCR CC(:,2) = Imported_Matrix(:,2); % delta Q CC(:,3) = Imported_Matrix(:,3); % Q initial CC(:,4) = Imported_Matrix(:,4); % Q final

A = [39.098 1 39.098; 19.023 1 19.023; 54.938 2 27.469; 1.008 1 1.008; 17.007 -1 -17.007; 96.056 -2 -48.028; 18.001 0 NaN]; K_M = A(1,1); H3O_M = A(2,1); Mn_M = A(3,1); H_M = A(4,1); OH_M = A(5,1); SO42_M = A(6,1); H2O_M = A(7,1); K_Q = A(1,2); H3O_Q = A(2,2); Mn_Q = A(3,2); H_Q = A(4,2); OH_Q = A(5,2); SO42_Q = A(6,2); H2O_Q = A(7,2);

MCR = CC(:,1);%[-38.16551108 -20.59608948 14.80389713 - 57.55481731 -57.34009381 1.308374229 -21.62639297];%put all the MCRs in here. A_cat = NaN(length(MCR)); %need a better rxn_names = {'K-H2O','H-H2O','K+H2O','K+H','H+H2O','K+H3O','K- OH','H-OH','K-SO4','H-SO4'}; for i = 1:length(MCR)%Find the slope for each possible equation for each MCR and store them. i = individual MCR slope(1,i) = ((K_M+MCR(i))/H2O_M); %Potassium and Water in opposite directions slope(2,i)= ((H_M+MCR(i))/H2O_M); %Protons and Water in opposite directions

207

slope(3,i) = -((K_M+MCR(i))/H2O_M); %Potassium and Water in the same direction slope(4,i) = -(K_M+MCR(i))/(H_M+MCR(i)); %Potassium and Protons in the same direction slope(5,i) = -((H_M+MCR(i))/H2O_M); %Protons and Water in the same direction slope(6,i) = -(K_M+MCR(i))/(H3O_M+MCR(i));%Potassium and Hydronium in the same direction slope(7,i) = (K_M+MCR(i))/(OH_M+MCR(i)); %Potassium and hydroxyls in the opposite directions slope(8,i) = (H_M+MCR(i))/(OH_M+MCR(i)); %Protons and hydroxyls in the opposite directions slope(9,i) = (K_M + MCR(i))/(SO42_M+2*MCR(i)); %Potassium and sulfates in opposite directions slope(10,i) = (H_M + MCR(i))/(SO42_M+2*MCR(i)); %Protons and sulfates in opposite directions

for j = 1:length(slope)%now find y-values for each possible equation %j is for the reaction equation %now separate it based on the sign of the charge passed if CC(i,2) < 0 %this assumes a mass gain for a negative MCR, filters for the cathodic cycle row = 1; x_Cat = [-2.1:0.25:-0.1]'; for k = -2.1:0.25:-0.1%limited to X > 0 for the anodic cycle MCR_neg(i) = CC(i,1); if (k*slope(j,i)) < 0 solns_neg_Q(row,j,i) = [k.*slope(j,i)]; row = row +1; else solns_neg_Q(row,j,i) = NaN; row = row +1; end end figure(i) set(gca,'fontsize',12); c = jet(length(slope)); plot(x_Cat,solns_neg_Q(:,j,i),'linewidth',2,'DisplayName',rxn_na mes{j},'Color',c(j,:))

legend('show','Location','best') title(['Cathodic. MCR ' num2str(MCR_neg(i))]);% Select peak maxima starting after the 1st minimim, and the last data point.');

208

xlabel('a (mol)') ylabel('b (mol)') hold on f_n = "cath_MCR"+num2str(round(MCR_neg(i))); saveas(gcf,f_n,'png') else

row = 1; x_Ano = [0.1:0.25:2.1]'; for k = 0.1:0.25:2.1%limited to X > 0 for the anodic cycle MCR_pos(i) = CC(i,1); if (k*slope(j,i)) > 0 solns_pos_Q(row,j,i) = [k.*slope(j,i)]; row = row +1; else solns_pos_Q(row,j,i) = NaN; row = row +1; end end figure(i) set(gca,'fontsize',12); c = jet(length(slope)); plot(x_Ano,solns_pos_Q(:,j,i),'linewidth',2,'DisplayName',rxn_na mes{j},'Color',c(j,:))

legend('show','Location','best') title(['Anodic. MCR ' num2str(MCR_pos(i))]);%'FontSize',12);% Select peak maxima starting after the 1st minimim, and the last data point.'); xlabel('a (mol)') ylabel('b (mol)') hold on f_n = "ano_MCR"+num2str(round(MCR_pos(i))); saveas(gcf,f_n,'png') end end end

% %put the data into files and save it %%

anodic_eqns = cell(length(solns_pos_Q)+1,length(rxn_names)*length(MCR_pos)); for n=1:length(MCR_pos) anodic_eqns{1,10*n-9}=MCR_pos(n);

209

for rxn=1:length(rxn_names) anodic_eqns(2,rxn+10*n-10)=rxn_names(rxn); end end for tq = 1:length(MCR_pos) for j = 1:length(solns_pos_Q)-1 for k = 1:length(rxn_names) anodic_eqns(j+2,k+tq*10- 10)=num2cell(solns_pos_Q(j,k,tq)); end end end cathodic_eqns = cell(length(solns_neg_Q)+1,length(rxn_names)*length(MCR_neg)); for n=1:length(MCR_neg) cathodic_eqns{1,10*n-9}=MCR_neg(n); for rxn=1:length(rxn_names) cathodic_eqns(2,rxn+10*n-10)=rxn_names(rxn); end end for tq = 1:length(MCR_neg) for j = 1:length(solns_neg_Q)-1 for k = 1:length(rxn_names) cathodic_eqns(j+2,k+tq*10- 10)=num2cell(solns_neg_Q(j,k,tq)); end end end filename1 = strcat('anodic_',FileName(1:11),'.xls'); filename2 = strcat('cathodic_',FileName(1:11),'.xls'); xlswrite(filename1,anodic_eqns); xlswrite(filename2,cathodic_eqns);

210

Appendix C

Peak Fitting Instructions for Birnessite Data

C.1 Raman Data:

C.1.1 Getting the data into Origin

Make a workbook with a separate sheet for each spectrum. Title the book with the electrode name and which electrolyte it was cycled in. On each sheet, label something (the comment of one of the columns, or the sheet title) the potential and whether it’s anodic or cathodic. Ex: “0a” or

“100a” to show 0 V vs. Ag/AgCl during the anodic cycle, or 0.1 V during the anodic cycle. This will help later when you’ve fit 16 different curves and need to remember which potential and sweep direction each corresponds to.

Col A is the Raman shift

Col. B is the intensity

Do not normalize

Subtract the data that occurs before the noise from the electrolyte (in my K2SO4 electrolyte, I deleted all data points before ~ 60 cm-1).

C.1.2 Background Subtraction

Select the intensity column (Column B) for a spectrum and open the Peak Analyzer (Analysis →

Peaks and Baseline → Peak Analyzer → Open Dialogue). In the dialog window, select:

Goal: Subtract Baseline

Click “next” and define the baseline according to the settings in Figure 1.

211

Figure 1. Baseline mode settings for background subtraction. Baseline Mode: user defined.

Baseline analysis points: 1st and 2nd derivative zeros. Smoothing window size: 30. Polynomial order: 4. Threshold: 0.05. Points: 4.

Click “find” and “next”. The program may fit some points that are not in the baseline (Fig. 2).

212

Figure 2. Baseline points not in the dataset baseline. The third point needs to be moved.

Use the settings in Figure 3 for the baseline creation. If any of the points are not in the bottom of the data as in Figure 2, use “Modify/Del” to move them to a more appropriate position.

213

Figure 3. Settings for baseline creation. Connect points by interpolation, keep the number of baseline points the same as the input data, and use a spline for the interpolation method.

You can now hit “finish”, and Origin will take you back to your workbook. Column D is now your working data column, label this in the “Comments” with the same identifier as you previous labeled this curve (example in Fig. 4).

Figure 4. Example curve heading after baseline subtraction. 214

C.1.3 Peak Fitting

Once you have subtracted the baseline for each Raman spectrum, you can begin fitting the peaks. Select your background-subtracted data column and open the Multiple Peak Fit dialog

(Analysis → Peaks and Baseline → Multiple Peak Fit → Open Dialog).

Select the Lorentz function for peak fitting and hit “ok”. Maximize the graph that pops up and select 4 peaks as in Figure 5 (approximately near ν4, ν3, ν2, and ν1, in order). At 0 V, the peaks for ν4 and ν1 will be more shoulders than anything else. Try to select the center of the peaks for these, but you can eyeball it some. Make sure you select the peaks in the same order for each spectrum. After you select the 4 peaks, click “Open NLFit”.

Figure 5. An example of where to select the peaks.

215

These spectra can tricky and will not always fit well if you have the software iterates automatically. The ν3 and ν1 peaks most often need manual adjustments. We do not extract any data from the ν4 peak, it just helps the fit converge. In the NLFit dialog, I step through the first few iterations using the “1 iteration” button circled in green in Figure 6. While you do this, watch the graph to make sure that all the peaks look reasonable. I often find that if they start getting very wide, or shifting to areas with no obvious peak, I have to “fix” either the width (my first choice), or the center (if they’ve moved way off) for a few iterations until everything starts behaving again.

I do this by checking the “Fixed” box for the given row, and then changing the Value. Raman peak widths are typically narrow, I will set mine between ~25-80. Once the overall positions reasonably match what we see and expect, uncheck any fixed values and keep stepping through one iteration at a time. Once the peak values are not changing much in an iteration, you can hit the “Fit until converged” button next to the “1 iteration” button.

Figure 6. The NLFit dialog. Use the circled “1 iteration” button and make minor adjustments as needed to peak width and center until the peaks stop moving much. 216

C.1.4 Data Compilation

Once you have fit all the peaks, we need the peak center and height values for the ν2 and

ν1, peaks, as well as the standard deviations of each. This will allow us to track the variation in peak center as a function of potential, as well as the intensity ratio of ν2/ν1. At this point, I find it easiest to take these values in Figure 7 and copy them into Excel so I can organize them and paste them back in as in Figure 8.

Figure 7. Calculated parameters from the peak fitting.

Figure 8. Final Origin worksheet with the calculated data.

217

C.1.5 Graphing

The final step is to graph the data. Make sure the graphs are titled clearly with correct axes.

Here, you want several different graphs:

1. Compare the raw data to the cumulative peak fit for each spectrum. Make one graph

each of anodic and cathodic, with the data points stacked as in Figure 9.

2. Normalize the cumulative fit peak for each potential, and graph them all (starting with

0V anodic at the bottom, going up to 0 V cathodic) as in Figure 10.

3. The peak centers of ν1 vs. Ewe as line + symbol plots, including error bars. Use the same

color but make the symbol size 3 points, and have the anodic cycle symbols closed and

cathodic cycle symbols open. The error bars should have a line width of 1 and a cap

width of 3. See Figure 11.

4. The peak centers of ν2 vs. Ewe as in Figure 11.

5. The ratio of ν2/ν1 vs. Ewe as in Figure 11, without the error bars NormalizedIntensity (a.u.)

200 400 600 800 1000

Raman Shift (1/cm)

Figure 9. Comparing the raw Raman data with the cumulative fit peak at each potential.

218

Normalized Intensity (a.u.)

200 400 600 800 1000 -1 Raman shift (cm )

Figure 10. Normalized cumulative fit Raman spectra for the whole cycle.

655

650

645

640 ν1 center

635

630 0.0 0.2 0.4 0.6 0.8

Potential (V vs. Ag/AgCl) Sheet2 Figure 11. Calculated Raman peakν1 center center graph. D G

C.2 X-ray Diffraction Data:

Steps 1-2 (getting the data into Origin, and background subtraction) are the same for XRD data as for the Raman data.

For peak fitting, use the PseudoVoightII function, with 3 peaks.

219

Data compilation is the same, but now you want to pull out the following info to make the summary graphs:

• Maximum intensity of each (001) peak so you can normalize them

• Peak centers: °2θ for the (001), (002), and (Au) peaks

• Interlayer spacings: Å for (001), (002), and (Au) peaks (use Bragg’s law; Cu-kα

radiation)

For graphing:

1. Graph a 2-y plot of the (001) peak and Au peaks vs. Ewe, like Figure 11. (001)

should go on the left axis, Au on the right. Do this for both the peak position (°2θ)

and the lattice parameter value (Å).

2. Normalize each background-subtracted dataset by the maximum intensity of the

(001) peak, and plot these to show the progression of the full spectrum with time,

with 0V anodic at the bottom, as in Figure 12.

3. Zoom the above graph in to just show the (001) peak, as in Figure 13.

Intensity(a.u.)

10 15 20 25 30 35 40

2θ (°)

Figure 12. Full XRD pattern of the birnessite electrodes

220

Figure 13. Zoomed-in XRD showing the (001) peak of the birnessite.

221

Appendix D

Effect of Film Thickness on the Behavior of Birnessite

As mentioned in Chapter 4, the KMnO4 + KCl birnessite electrodeposition solution spontaneously precipitates MnO2, which leads to varying electrode morphology. Figure 4 in

Chapter 4 shows islands, which vary in density depending on the location on the current collector relative to the electrical connection, the “age” of the deposition solution, and the length of time the electrode was left in the solution after deposition ended. When first taken out of the deposition solution and rinsed, all samples had a dark red color with some slight rainbowing, indicating their thinness. After drying, samples deposited from a fresh solution and removed soon after the electrodeposition finished retained some of the red coloring. On the other hand, samples from a previously used solution or left in the solution overnight dried into a brown color. The amount of color change after drying corresponded to the size of the islands visible after drying—a reddish color was indicative to a more uniform film with few islands, while a brown color corresponds to larger islands.

I was unaware of the extent of this variation until after the lab shutdown in March 2020, while analyzing the EQCM data I took in February on an 0.68 mg birnessite film. Most behavior reported in the literature and briefly described in Table I shows a linear change similar our data in

Chapter 4. However, this 0.68 mg film behaved in an unprecedented manner, as shown by the mass change and gCV 10 mV/s in Figure 1.

222

Table I. Summary of Birnessite EQCM Results from Literature Loading/ Claimed Sweep Electrolyte MCR(s?) Capacitance Potential Ref. Birnessite? Mechanism Rate 0.1 M 16.51 Na+ and H+ 579 F/g Na2SO4 0.2 M + + 2 17.22 Na and H 581 F/g 0.2-1.1 NaNO3 30 μg/cm 5 vs. 29 0.1 M unclear mV/s 7.41 Li+ 624 Ag/AgCl Li2SO4 0.1 M 20.07 K+ and H+ 525 K2SO4 0-0.8 V 0.5 M 50 μg/cm2; 20 21.6 Na+ N/A vs. 26 Na SO yes mV/s 2 4 Ag/AgCl + 1 M LiCl 16.2 H3O 204, 184 2 102 μg/cm ; + 10, 50 0.5 – 0.8 190 1 M NaCl 18.7 H3O 224, 199 no, ε-MnO2 mV/s (EQCM) + 1 M KCl 21.6 H3O 204, 183 0-0.8 V 0.1 M 16 μg/cm2; 5 195 @ 160 N/A H+ vs. 27 Na SO yes mV/s mV/s 2 4 Ag/AgCl ~ 0.67 C? 2.5 M Li+·3.8 Yes, thin 78 N/A LiNO H O 3 film 2 2.5 M - + 50/500 NO3 & Li 0-0.8 V LiNO3 5 140-160 nanofoam vs. 28 2.5 M - mV/s F/g w/coating NO3 Ag/AgCl NaNO3 N/A 40/1500 ~ half of 2.5 M nanofoam NO - 50/500 LiNO 3 3 w/coating foams -0.55- 3 H+ 1 M 40 0.95 V μg/electrode; N/A exchanges N/A 30 Na SO mV/s vs. 2 4 yes with K+ Ag/AgCl + 0.5 M Li ·nH2O 2 55 F/g 0-1 V LiClO4 400 μg/cm ; ± xH2O 20 several vs. 114 0.5 M yes K+·nH O - mV/s 2 53 F/g Ag/AgCl NaClO4 xH2O 0.44- 1 M 37 μg/cm2; 50 119 @ 8 1.44 V N/A Na+ 31 Na2SO4 yes mV/s mV/s vs. Ag/AgCl

223

Figure 1. EQCM behavior of a thick film in K2SO4 at 10 mV/s. A) The CV looks like a typical birnessite film, while the mass change shows regions of mass loss and gain. B) The gCV shows no clear relation to the CV, indicating that the mass changes may not be directly related to electrochemical events.

The mass change shows that there are three distinct regions in both the anodic and cathodic cycle, while the gCV in Figure 1B shows no clear relationship with the current. The MCR graph in Figure 2 shows that the beginning and end of each half of the cycle, the process is cation- dominated as in the literature. However, the middle section shows a mass increase with oxidation indicating an anion-dominated segment. These MCRs do not indicate that any individual ions were involved in the process, which led me to develop the Matlab script “QCM_solver” described in

Appendix B. This allowed me to calculate the potential reaction equations. Figure 3 shows the potential solutions for the anion-dominated region of the anodic cycle in Figure 2, where the MCR is 14 g/mol e-.

224

Figure 2. Potential and mass vs. charge of a thick film in K2SO4 at 10 mV/s.

Figure 3. Potential solutions for the region of charge storage in a thick birnessite film where the

MCR equals -14.8 g/mol e- during the anodic cycle.

Now, it is possible for this region to show an increase in mass if significantly more water molecules enter the film than cations leave it. Regardless, to my knowledge this behavior has only been seen once before in birnessite: when Beasley et al. conducted an EQCM study of thick

225

electrodes, consisting of birnessite deposited onto a thick carbon foam.123 They claim it was due to anion ad(de)sorption. My hypothesis is that the additional flexibility the isolated birnessite islands have in-plane with the electrode allows greater volume changes with the accommodation of hydrated anions onto the surface. On the other hand, it is possible that the morphology variations and heavy mass of the film make it too complex to be analyzed with traditional EQCM.

For the purposes of this appendix, I simply want to illustrate the differences I observed in the behavior of birnessite films with thickness. In addition to the 0.68 mg film described above, I electrodeposited two thinner films with mass loadings of 0.024 and 0.18 mg. Data from with the

0.18 mg film is discussed in Chapter 4. However, comparing a bare gold electrode with these three films suggests that the pseudocapacitive behavior of birnessite is partially due to the averaged response of many redox couples with varying site energies. Figure 4 shows the gCVs of the gold electrode and three birnessite films at 50 mV/s in K2SO4. In A), the gold background shows typical

EDL butterfly behavior. The CV is capacitive except for an OER peak at the anodic potential, and a substrate peak around ~0.2 V. The 0.024 mg film in B) shows three sets of peaks in its gCV, while the 0.18 mg sample in C) exhibits the “typical” birnessite behavior and the 0.68 mg sample in D) shows two peaks during the anodic cycle and one in the cathodic. It is unclear whether the apparent 4th set of peaks near the cathodic turnover potential in Figure 4B is due to a physical process or is just a remnant of filtering the derivative data. In the very thin 0.024 mg sample I expect most of the interlayer of the material to be directly in contact with the electrolyte. The presence of multiple peaks in this gCV suggests to me that there are several site energies for ion redox. The disappearance of these peaks in the thicker sample may be explained by the reduction in surface area : volume with film thickness. As this ratio decreases, more ions must diffuse through the layers of birnessite flakes to get to their redox sites, introducing a kinetic limitation

226

for surface and interlayer redox. This then spreads out the redox potential in one broad peak. This tread is also shown somewhat in the AFM dilatometry data described in Chapter 4.3.2, where the

CV shows a single peak while multiple peaks are visible in the mCV. In the thickest sample, the gCV in the anodic cycle shows two peaks, like the mCV, while only one is visible around the interlayer potential in the cathodic cycle. I think the anodic peaks suggest that in the thicker sample surface behavior again plays a significant role. In the cathodic cycle, the butterfly-shaped surface behavior is overwhelmed by the interlayer redox, which is more kinetically limited as discussed in

Chapter 4. While more work must be done on the relationship between film thickness and charge storage behavior of birnessite, these results appear to indicate that there may be an ideal electrode thickness where the interplay of surface and interlayer redox leads to an optimal electrode behavior. Further research into this, such as synchrotron XRD and additional AFM studies may help show whether the pseudocapacitive CV is indeed due to the averaging of several redox couples.

227

Figure 4. gCVs at 50 mV/s in K2SO4 of A) the gold EQCM crystal, B) the 0.024 mg birnessite film, C) the 0.18 mg birnessite film, and D) the 0.68 mg birnessite film.

228