Designing Electric Field Assisted Catalytic Reactors for Hydrogen

DESIGNING ELECTRIC FIELD ASSISTED CATALYTIC REACTORS FOR HYDROGEN

PRODUCTION APPLICATIONS

JAKE T. GRAY

A dissertation submitted in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY

WASHINGTON STATE UNIVERSITY The Gene and Linda Voiland School of Chemical Engineering and Bioengineering

DECEMBER 2019

To the Faculty of Washington State University:

The members of the Committee appointed to examine the dissertation of JAKE T. GRAY find it satisfactory and recommend that it be accepted.

Su Ha, Ph.D., Chair

Norbert Kruse, Ph.D.

Jean-Sabin McEwen, Ph.D.

M. Grant Norton, Ph.D.

ii ACKNOWLEDGMENT

This dissertation would not have been possible without the assistance of a great many people—far too numerous to name, and many of whom I do not know. Let the rudimentary list that follows suffice, and accept my sincerest apologies for anyone inadvertently overlooked.

I first gratefully acknowledge my funding sources, without whom this research would only have been an idea. Most of the work presented in this dissertation had its beginnings in my project as an undergraduate, which was financed in part by the DeVlieg Foundation and many of the supplies and equipment used throughout this dissertation were obtained through their generosity.

The National Science Foundation Graduate Research Fellowship Program (NSF-GRFP Award

#1347973) contributed to most of the rest of this work by directly supporting me as a researcher.

Without this aid, I would not have been able to focus on research. Additional funding from the

Korea Institute of Energy Research and from the U.S. Office of Naval Research helped to purchase more supplies and equipment as the research progressed and allowed the project to expand through collaboration with the Navy Undersea Research Program.

The intellectual input of my committee drove this research forward: I thank Drs. Su Ha,

Norbert Kruse, Jean-Sabin McEwen, and Grant Norton for their academic assistance, advice, and general support. I’d like to extend additional gratitude to Drs. Ha and Norton for their assistance in preparing my NSF-GRFP and Graduate Research Internship Program (GRIP) application packages.

I gratefully acknowledge the involvement of numerous collaborators over the years: Dr.

Fanglin Che for her detailed and insightful density functional theory support which was the progenitor of much of my work, and supplemented much of the rest; Kriti Agarwal for her

iii assistance with the electrical engineering aspects of this research and COMSOL modeling work;

Dr. John Izzo for his support and guidance while working at the Naval Underseas Warfare Center which helped to expand the project in new directions; and to the undergraduate students who worked closely with me to adapt new materials for this application: Matt Sundheim and Derek

Burnett.

Without our lab and office facilities and equipment and the people responsible for holding it all together, none of this research would have been possible. Although I am immensely grateful to the entirety of the WSU faculty and staff for their role in maintaining our facilities, I would like to recognize certain people specifically: Jim Pogue, Jennifer Starks, and Nicole Leavitt for always putting up with my complicated schemes, ordering my equipment and supplies, and recovering my travel expenses; Jo Ann McCabe for helping navigate the twisted labyrinth that is university finances; Burton “Billy” Schmuck for looking out for our safety and the safety of the community;

Kate Konen for her patient help with all things technological (even if it was usually just a button we forgot to press); Samantha Bailey for taking care of the crucial behind-the-scenes bureaucratic headaches of graduate school; and to Valerie Lynch-Holm and Daniel Mullendore at the Francesci

Microscopy and Imaging Center for training, advice, and keeping the microscopes in excellent condition despite the hordes of inconsiderate graduate students always fiddling with them.

To my group members, past and present, I thank you for companionship both inside and outside the lab. Thanks for making graduate school slightly more tolerable: Xiaoxue “Christy”

Hou, Shuozhen Hu, Tsai Garcia-Perez, Bita Khorasani, Parissa Ziaei, Qusay Bkour, Kaytee

Villafranca, Xianghui “John” Zhang, Kai Zhao, Oscar Marin-Flores, Martinus “Martin” Dewa,

iv Wei-Jyun “Will” Wang, Yilin Liu, and Mohamed “Mo” Elharati. I wish you all success and happiness wherever your paths may lead.

To my friends outside the lab, thanks for helping keep me grounded and limiting the amount of time I spend thinking about research. I especially thank Justin Jurgerson for being an entertaining conversationalist, formidable board game adversary, and delightful dinner guest.

For my family I am eternally grateful. You have supported me since childhood and I wouldn’t be half the man I am today without you. My mother, Corrina Gray; brother Aric Gray

(and his wonderful wife, Jackie Gray); sister Caitlin Gray; and all of my grandparents: Sam and

Debbie Duncan and Kent and Susan Gray. Although they are no longer here to appreciate it, I also acknowledge the family I lost during my graduate journey: my great-grandmother Edith Curtis; my grandmother Carolyn Pray; and my father, Loren Travis Gray. Despite my best efforts to drown myself in my work, you have always reminded me of what is most important in life.

Finally, I thank my partner-in-crime, Julian Reyes. Your smile always brightens my day whether we’re getting lost in the mountains or getting fat together on the couch.

v DESIGNING ELECTRIC FIELD ASSISTED CATALYTIC REACTORS FOR HYDROGEN

PRODUCTION APPLICATIONS

Abstract

by Jake T. Gray, Ph.D. Washington State University December 2019

Chair: Su Ha

Fundamental studies on the effects of strong electric fields (on the order of 1-10 V/nm) have been conducted in various forms for nearly a century. These investigations have revealed a surprising amount about the natural world: the presence of strong intrinsic electric fields is, in part, responsible for the high catalytic activity of many natural systems. Examples include catalysts ranging from enzymes for biochemical processes to zeolites in industrial-scale petroleum refining to frustrated Lewis acid-base pairs in specialized synthetic chemistry. With Nature as our inspiration, attempts at artificially recreating these highly reactive conditions have been ongoing

(albeit sporadically) since at least the 1970s. Until recently, these experiments have been necessarily conducted in high-vacuum systems to avoid the dielectric breakdown associated with long-range high-intensity fields. A handful of attempts at high-pressure, high-throughput applications of this phenomenon have been attempted—but aside from a few promising observations, little progress has been made.

vi Herein are presented recent contributions to this body of work focusing on the development of (i) new high-pressure, high-throughput, and high-field reactors for hydrogen-producing reactions and (ii) tools for future reaction engineers seeking to incorporate applied electric fields into their designs. To this end, Chapters 1 and 2 supply comprehensive foundational knowledge including the fundamental physics of electric field assisted catalysis as well as previous attempts at reactor or test apparatus design. Chapter 3 explores the mechanism for the hydrogen producing reaction of formic acid decomposition. This well-characterized reaction is then applied in Chapter

4 as a reactive probe to directly measure the applied field strength at catalyst active sites. A technique is also presented for visualizing the field structures generated across the catalyst.

Chapters 5 and 6 delve deeper into more traditional hydrogen producing reactions via hydrocarbon steam reforming: methane in Chapter 5 and gasoline, diesel, and jet fuel surrogates in Chapter 6.

Two reactor designs are investigated in detail throughout this dissertation: the integrated circuit reactor in Chapters 4 and 5 and the coaxial capacitor reactor in Chapter 6. Suggested next steps for future researchers are provided in Chapter 7.

vii

TABLE OF CONTENTS

Page

ACKNOWLEDGEMENT ...... iii

ABSTRACT ...... vi

LIST OF TABLES ...... xi

LIST OF FIGURES ...... xii

PREFACE ...... 1

CHAPTER 1: INTRODUCTION ...... 3

Section 1.1. Transport ...... 3

Section 1.2. Molecular Orientation ...... 7

Section 1.3. Electronic Structure ...... 10

Section 1.4. Kinetic and Thermodynamic Changes ...... 16

Section 1.5. Intrinsic or Natural Field-Enhanced Catalysis ...... 20

CHAPTER 2: PRINCIPLES OF EFAC REACTOR DESIGN ...... 23

Section 2.1. The Field Emission and Field Ion Microscopes ...... 24

Section 2.2. The Scanning Tunneling Microscope ...... 33

Section 2.3. The Probe-bed-probe Reactor ...... 38

Section 2.4. The Capacitor Reactor ...... 57

Section 2.5. The Integrated Circuit Reactor ...... 66

CHAPTER 3: INVESTIGATING FORMIC ACID DECOMPOSITION...... 75

Section 3.1. Surveying the HCOOH Decomposition Mechanistic Literature ...... 76

Section 3.2. Experimental Analysis of HCOOH Decomposition ...... 78

viii Section 3.3. Developing a Holistic HCOOH Mechanism...... 82

Section 3.4. Simulating HCOOH Decomposition ...... 89

Section 3.5. Comparing Experiment and Simulation...... 95

Section 3.6. Implications of the Mechanism for EFAC ...... 95

CHAPTER 4: ESTIMATING AND VISUALIZING THE FIELD USING REACTIVE FORMIC

ACID PROBES AND SEM IMAGING ...... 99

Section 4.1. Predicting Field Strength ...... 101

Section 4.2. Measuring Field Strength using Thermodynamics ...... 103

Section 4.3. Modeling Surface Field Physics ...... 107

Section 4.4. Field Visualization and Mapping ...... 109

Section 4.5. Combining Techniques ...... 113

CHAPTER 5: METHANE STEAM REFORMING IN AN ICR ...... 115

Section 5.1. Experimental Details ...... 116

Section 5.2. Post-Reaction Characterizations of Spent Catalysts ...... 116

Section 5.3. Discussion ...... 120

Section 5.4. Implications for MSR EFAC Processes ...... 123

CHAPTER 6: PULSED-FIELD CCR DESIGN AND TESTING ...... 127

Section 6.1. Catalyst Preparation ...... 131

Section 6.2. Experimental Setup ...... 132

Section 6.3. Results ...... 134

Section 6.4. Discussion ...... 137

CHAPTER 7: FUTURE DEVELOPMENTS ...... 144

Section 7.1. Detailed Investigations of Logistic Fuel Reforming ...... 146

ix Section 7.2. Hydrocarbon Structural Considerations ...... 146

Section 7.3. Electric Field Structure and Impact on EFAC ...... 148

Section 7.4. Prevention of Sulfur Poisoning using Applied Electric Fields ...... 151

Section 7.5. Economic Advantages to an EFAC System...... 152

Section 7.6. Other Applications for EFAC ...... 153

Section 7.7. Detailed Microkinetic Studies of the EFAC of Formic Acid ...... 157

Section 7.8. Cross-validation of Reactors ...... 158

REFERENCES ...... 159

APPENDIX A: THE BERGMANN EQUATION ...... 180

APPENDIX B: FORMIC ACID AS FUEL ...... 192

APPENDIX C: HYDROCARBON REFORMING ...... 199

APPENDIX D: CCR PHYSICS DERIVATIONS ...... 203

LIST OF TABLES

Page

Table 1.3.1. Field Structure as a Result of Source Geometry ...... 12

Table 2.3.2.1. Details of the Sekine Group Work on Probe-Bed-Probe Reactors ...... 42

Table 3.2.1.1. Purpose of Formic Acid Decomposition Experiments ...... 79

Table 3.4.1. Monte-Carlo Model User Inputs ...... 90

Table 4.1.1. Electric Moment Calculation for the Decomposition of Formic Acid ...... 101

Table 5.4.1. Methane Steam Reformer Duty Reliance on Reactor Conditions ...... 125

Table 6.4.1. Predicted and Measured Surface Electric Fields for a Coaxial Capacitor Reactor .139

Table 7.2.1. Options for Testing Alkane Structure Interaction with Fields ...... 148

LIST OF FIGURES

Page

Figure 1.1.1. Surface Field Definitions ...... 4

Figure 1.1.2. Field-Driven Oxidation of Rh ...... 6

Figure 1.2.1. Rotational Acceleration Experienced by Molecules in a Field ...... 8

Figure 1.2.2. Water Adsorption and Deprotonation on Ni in Applied Fields ...... 9

Figure 1.3.1. Molecular Orbital Energy Changes in Strong Electric Fields ...... 14

Figure 1.4.1. Thermodynamic and Kinetic Changes in Formic Acid Decomposition ...... 18

Figure 2.1.1.1. The Field Ion Microscope ...... 27

Figure 2.1.1.2. Imaging a Pt Sample in the Field Ion Microscope ...... 28

Figure 2.2.1.1. The Scanning Tunneling Microscope ...... 35

Figure 2.3.1.1. The Probe-Bed-Probe Reactor ...... 39

Figure 2.3.2.1. Sekine Group Publications on Probe-Bed-Probe Reactors ...... 41

Figure 2.3.2.1.1. Characteristics of a Normal Plasma ...... 45

Figure 2.3.2.2.1. Effects of Charging in a Dusty Plasma ...... 48

Figure 2.3.2.2.2. Structure of a Dielectric Barrier Discharge ...... 49

Figure 2.3.2.3.1. Electrical Parameters Used in Probe-Bed-Probe Reactors ...... 51

Figure 2.3.2.3.2. Dielectric Breakdown in a Probe-Bed-Probe Observed by Oshima et al...... 54

Figure 2.3.3.1. Field Structure around a Particle in a Probe-Bed-Probe Reactor ...... 56

Figure 2.4.1. Capacitor Geometries ...... 59

Figure 2.5.1.1. A Simple Circuit Diagram ...... 67

Figure 2.5.1.2. Field Structure outside a Current-Carrying Wire ...... 68

xii Figure 2.5.1.3. Catalyst Placement in a Simple Integrated Circuit Reactor ...... 70

Figure 2.5.1.4. Surface Charge Distribution in a Capacitor-Arm Integrated Circuit Reactor ...... 71

Figure 2.5.2.1. Microkinetic Model of Methane Steam Reforming Developed by Che et al...... 73

Figure 3.1.1. Representative Mechanisms for Formic Acid Decomposition from Literature ...... 77

Figure 3.1.2. Rotation of Surface-Adsorbed Formate Fragments During Reaction ...... 78

Figure 3.2.2.1. Results for Formic Acid Decomposition over Mo2C on Graphene ...... 82

Figure 3.3.2.1. Mechanism for Formic Acid Decomposition over Mo2C on Graphene ...... 89

Figure 3.4.1.1.1. Calibration of the Monte-Carlo Model ...... 92

Figure 3.4.2.1. Monte Carlo Simulation Results ...... 94

Figure 3.6.1. An EFAC Analysis of the Proposed Mechanism ...... 96

Figure 4.1.1. Estimates of Formic Acid Selectivity in Applied Fields ...... 103

Figure 4.2.1.1. Experimental Setup for Field-Assisted Formic Acid Decomposition over Ni ....104

Figure 4.2.3.1. Field-Assisted Formic Acid Decomposition over Ni Results at 350 °C ...... 106

Figure 4.3.1. COMSOL Modeling of Electric Fields on a Ni Particle/Ni Foam Catalyst ...... 108

Figure 4.4.2.1. Image Brightening in the SEM due to Application of Negative Potential ...... 111

Figure 4.5.1. Correlation between Image Brightness and Measured Field Strength ...... 113

Figure 4.5.2. Topographical Field Mapping of a Ni Particle in a Ni Foam Pore ...... 114

Figure 5.2.1.1 X-Ray Diffractogram of Spent Ni Catalysts used in Methane Steam Reforming 117

Figure 5.2.2.1. SEM-EDS of Spent Ni Catalysts used in Methane Steam Reforming ...... 118

Figure 5.2.3.1. TPO of Spent Ni Catalysts used in Methane Steam Reforming ...... 119

Figure 5.3.1. Energetics of Methane C-H Bond Scission in a Positive Electric Field...... 121

Figure 5.3.2. Predictions for Oxygen Adsorbates on Nickel in the Presence of Electric Fields .122

Figure 5.3.3. Mechanism of Ni Oxidation in the Presence of Electric Fields Visualized ...... 123

xiii Figure 6.1. Possible CCR Configurations ...... 128

Figure 6.2. Field Strength at Catalyst Surface in a Coaxial Capacitor Reactor ...... 129

Figure 6.1.1. Socketed Ni Perovskite Particle Characterization ...... 132

Figure 6.2.2.1. Structure of tricyclo[5.2.1.02,6]decane (JP-10) ...... 133

Figure 6.3.1. Experimental Results for Formic Acid Decomposition in a CCR ...... 135

Figure 6.3.2.1. n-Dodecane Steam Reforming in a Coaxial Capacitor Reactor ...... 136

Figure 6.3.3.1. Isooctane Steam Reforming in a Coaxial Capacitor Reactor ...... 136

Figure 6.3.4.1. JP-10 Steam Reforming in a Coaxial Capacitor Reactor ...... 137

Figure 6.4.1. Characteristics of a Pulsed Voltage Source ...... 138

Figure 6.4.2. Correlating Predicted Gibbs Energy Changes and Experimental Measurements ..142

Figure 7.2.1. Linear Dependence of Alkane Polarizability on Total Number of Bonds ...... 147

Figure 7.3.1. Latin Square Design for Pulse Reactor Experiments ...... 150

Figure 7.6.1.1. Thermodynamic Predictions for Methanol Steam Reforming ...... 154

Figure B1. The Closed Carbon Cycle of Formic Acid Decomposition ...... 192

Figure D1. Geometry and Equivalent Circuit of CCR with Dual Dielectrics ...... 203

Figure D2. Gaussian Surface used for CCR Analysis ...... 204

xiv

In memory of L. Travis Gray.

(1968-2018)

xv PREFACE

At dinner following my undergraduate commencement, my father—a graphic designer by trade—proclaimed his disappointment that he wasn’t able to provide me with any professional skills while growing up that would be useful in my chosen career. I found this viewpoint so shocking that I had a difficult time responding. Engineering, like art, is a creative discipline: engineers must be able to approach problems from unique angles to develop new solutions. An artistic background produces better scientists, better engineers, and a better world.

Neither engineering nor science are art, however, and a creative idea is not necessarily a viable one. After all, a random assortment of pipes and knobs is a sculpture, not a refinery.

Engineering is the creative application of science—engineers walk the tightrope between science and art. Although we dare to dream of things that never were, our thinking must remain rooted in reality.

The work presented in this dissertation is the result of years of creative endeavor that requires an understanding of disciplines unfamiliar to a traditionally trained chemical engineer including electrostatics and electrodynamics. This dissertation occupies the space between chemical engineering, physical chemistry, and electrical engineering. Working in this space requires one to understand all three disciplines—but not necessarily to master them. I have relied heavily on the input of my collaborators in this regard, experts in their respective fields, and have always sought a way to “bridge the gap” by simplifying complex principles and highlighting obscure ones. I have attempted, therefore, to provide thorough enough descriptions of the physical phenomena underpinning electric field assisted heterogeneous catalysis and how these interface with more traditional reaction engineering principles such that a new researcher in chemical

1 engineering can begin to work with and design such systems. These principles have been invaluable in my work and it is my hope that this dissertation will be useful to future enterprising engineers in their own electric field assisted chemistry designs. Hence, the dissertation body chapters are not merely reproductions of published works, but distilled and focused with the intent of providing the reader with new insights to this body of work that would not otherwise be generally available.

For topics that are important but tangentially related to the main dissertation body I have provided citations to comprehensive books or reviews on the subjects rather than performing a comprehensive review myself (for example, naturally arising fields discussed in Chapter 1). In areas that are more directly related to the dissertation work I have attempted to provide a more detailed breakdown of the literature—this is done in the case of the probe-bed-probe reactor in

Chapter 2, for example, which is an immediate precursor to my own reactor designs. The experiments suggested in Chapter 7 are intended as a summary of natural next steps to continue the work presented in this dissertation. I leave it up to future researchers to determine the details of how to approach these experiments, but where possible I have provided preliminary calculations, data, and supporting literature as a guide.

CHAPTER 1: INTRODUCTION

In this first chapter we discuss the fundamentals of electric field assisted catalysis (EFAC) with a focus on the direct effects of a strong applied field on chemical systems. The reader is encouraged to consider the complexities that may arise from the interplay of these phenomena, as these complex interactions are responsible for much of the observations made throughout this work. Sections are presented in order of increasing conceptual difficulty rather than by relevance to heterogeneous catalytic processes. We begin with a discussion of specific physical phenomena including ionic transport in electric fields (Section 1.1), molecular orientation changes of polar molecules in electric fields (Section 1.2), and electronic configurational changes of molecular orbitals and band structures in electric fields (Section 1.3). The net effect of an applied electric field on the thermodynamic and kinetics of a chemical reaction is investigated in Section 1.4, and

Section 1.5 concludes by examining some areas where this phenomenon is observed in nature.

In the interest of balancing the perspectives of pure and applied sciences, examples of real- world and potential applications are presented alongside descriptions of the fundamental scientific principles underpinning EFAC. Our hope is that this will aid the reader in developing a deeper understanding of the complex and interesting scientific principles underpinning EFAC as well as its potential place in the chemical engineer’s toolbox as a reaction engineering technique.

Section 1.1. Transport

Perhaps the most easily understood interaction between chemical species and electric fields is that of ion migration. When ions in a solution are exposed to an electric field, they experience a force which accelerates them according to their charges, masses, and the direction of the field

(Figure 1.1.1). Diffusion rates can therefore be manipulated in ionic systems simply by applying

3 an external electric field. Separations processes are also possible with ionic systems using the same principles. Electrophoresis, for example, is a common technique used for biomolecular analysis

(i.e. for proteins, DNA, and so on) that takes advantage of this principle.

Figure 1.1.1. (a) Electric field directions are defined by the force (arrows) experienced by an imaginary “test charge” (small circles) which is always positive. Since two positive charges repel, the field around a positive ion points away from the field source; while it points towards a negative field source since opposite charges attract. These field definitions will be used throughout the rest of this dissertation with respect to catalyst surfaces. (b) Whenever a “positive field” is mentioned, imagine a field line pointing away from a surface, and one pointing toward a surface for the term “negative field.”

Examples of ionic transport in heterogeneous reactions are less common, though several are known. Fuel cells rely on ion transport through a semipermeable membrane to complete chemical reactions while forcing electron exchange to occur via an external route, generating electrical work. Ion transport through proton exchange membranes or solid oxide fuel cells are significantly impacted by the presence of naturally occurring electric fields established by reactions at the anode and cathode of the cell. Applying an external electric field across the membrane further helps to facilitate ion transport and increase the cell’s energy output capacity

[1]. This may be a difficult technique to implement in practice, however, since an energy source

4 will be needed to establish such a field in the first place. Still, fuel cell membranes serve as a useful example of the role natural electric fields play in diverse chemical processes.

Ion transport manipulation by applied electric fields in heterogeneous catalytic processes are observed in the so-called “NEMCA” effect. NEMCA, or the Non-Faradaic Electrochemical

Modification of Chemical Activity, occurs over metallic nanoparticles supported on ionic conductors such as nickel on cerium (IV) oxide. These catalysts may experience a phenomenon known as “spillover” when exposed to an external electric field. During spillover, oxide anions from the support migrate onto the surface of the nanoparticle and promote oxidation reactions.

Ionic spillover facilitated by electric fields has been shown to significantly alter reaction behavior.

The NEMCA effect was first described by Stoukides and Vayenas in 1981 using the oxidation of ethylene over silver particles on yttria-stabilized zirconia (YSZ) [2]. It was found that with the application of, at most, ±2.5 V and 0.10-0.80 mA, the reaction rate of ethylene oxidation could be improved by two orders of magnitude while selectivity toward ethylene oxide could be increased by about 18%. Many other reactions and metal/support catalysts have since been shown to be significantly impacted using the NEMCA effect [3-7].

Ionic transport assisted by electric fields can also play a role in heterogeneous reactions over unsupported metallic catalysts. For example, the presence of a positive electric field facilitates the transport of oxide ions from the surface of a metal into the bulk crystal, thereby promoting oxidation of the catalyst [8, 9]. An example of this effect is shown in Figure 1.1.2. The inverse is also true: negative fields should prevent oxidation of a metal catalyst. This can be useful in two ways: first, the promotion of bulk oxide formation using a positive field can help to deter coke production in carbon-rich processes by creating an “oxygen reservoir” in the catalyst sub-sruface;

5 and second, processes which are susceptible to deactivation by oxidation can be protected by applying negative fields.

Figure 1.1.2. Field ion microscope (FIM) images of a Rh catalyst exposed to a mixture of H2 and O2 (a) without and (b) with an applied positive field indicates that oxidation of the surface occurs at high positive electric fields. (c) an atomic resolution FIM image of the same Rh tip showing active sites and the various crystallographic planes. (d) Density functional theory model used for computing the change in the activation energy barrier of removing an oxygen atom from the Rh subsurface in the presence of applied fields, which indicated that bulk Rh oxide formation is enhanced in a positive electric field. Taken from Ref. [8].

In summary, the application of an electric field to heterogeneous catalytic systems can significantly change the ionic flux behaviors of the system and thereby dramatically alter its reactive properties. Moreover, this phenomenon is easily understood using basic freshman physics: charges move in the direction to which they are attracted. In fact, the concept of ion manipulation using electric fields can be extended more generally to include a wider range of molecules by considering molecules with permanent dipole moments.

Section 1.2. Molecular Orientation

Molecules with permanent dipole moments can be affected by electric fields in much the same way as ions. Rather than inducing translational motion, however, the electric field induces rotational changes in polar molecules. As long as a molecule’s dipole moment is not aligned with the external electric field, it will experience a torque, τ. Rotational acceleration (α) of the molecule is therefore a function of the angle (θ) between the electric field and the dipole moment, the mass of the molecule (m), the size of the molecule, and the strengths of the electric field (‖F⃑ ‖) and dipole moment (‖p⃑ ‖):

τ = p⃑ × F⃑ = ‖p⃑ ‖‖F⃑ ‖ sin θ 1.2.1

2 τ = α ∑ m푖r푖 1.2.2 푖

Here, the summation term represents the moment of inertia, where r푖 is the distance from the axis of rotation to each atom (taken to be a discrete point) in the molecule. The axis of rotation can be determined by calculating the center of mass of the molecule. Smaller molecules with large dipole moments, having low inertia while experiencing a significant torque, will thus rotate freely and rapidly in an external electric field.

As an illustration, consider the three simple molecules shown in Figure 1.2.1. Water, which has a dipole moment of 1.85 Debye (D), ammonia with a dipole moment of 1.47 D, and hydrogen sulfide with a dipole moment of 0.97 D. Assuming the center of rotation of each to be about the relatively massive O, N, or S atoms, the only contributions to their moments of inertia are the small hydrogen atoms at a distance one (O/N/S)-H bond away. Taking the mass of a hydrogen atom to

7 be 1.673x10-27 kg, the length of the O-H bond to be 0.96 Å, a very small electric field of 1 V/m

(for simplicity) with the optimum dipole moment/electric field angle of 90°, an angular

17 -2 acceleration of 2.00x10 s will result. Similar calculations for ammonia (r푁−퐻 = 1.01 Å) and

16 -2 16 -2 hydrogen sulfide (r푆−퐻 = 1.34 Å) yield angular accelerations of 9.58x10 s and 5.42x10 s , respectively. Water is therefore twice as sensitive to the effects of an electric field as ammonia and four times as sensitive as hydrogen sulfide, despite apparently similar dipole moments and bond lengths in comparison with ammonia and structural similarities with hydrogen sulfide.

This analysis demonstrates that there are many factors which influence molecular behavior in an electric field, and even a phenomenon as simple as classical torque-induced rotation is strongly affected by small changes in molecular structure. At first glance one might assume that nonpolar molecules will experience no torque and should not rotate in the presence of an electric field. However, polarization of the molecules in the presence of the electric field establishes transient dipoles that are then acted upon by the field and may induce rapid configurational changes. The consequences of this influence molecule-surface interactions (Section 1.3) as well as the thermodynamics and kinetics of chemical reactions (Section 1.4).

Figure 1.2.1. Small changes in molecular structure can lead to large changes in angular acceleration due to an electric field as in this comparison between (from left to right) water, ammonia, and hydrogen sulfide. This illustrates how even very small structural changes can have a large impact in how molecules interact with an electric field.

So much for isolated molecules; what happens during heterogeneous catalysis when molecules are adsorbed on a metallic surface? Che et al. studied electric field assisted methane steam reforming over nickel metal and measured the presence of adsorbed water molecules and activated water (e.g. HO*) using ex situ X-ray photoelectron spectroscopy (XPS) [10]. The results of this experiment are shown in Figure 1.2.2a. Computational determination of the most likely orientations of adsorbed water molecules on the catalyst surface in the presence of positive and negative electric fields are shown in Figure 1.2.2b. Comparing these two figures gives a clear picture of what is occurring. The dipole moment of water extends through the center of the molecule, bisecting the angle formed by the two O-H bonds and pointing away from the O atom

(using the physicist’s definition of the dipole moment). Since the molecule reaches a stable configuration when its dipole moment is aligned with the field (θ = 0°), water in a positive field lines up with its O atom pointing toward the metal surface while in a negative field its H atoms point toward the surface. It may also be helpful to think of this in terms of electrons. The O atom of water is electron-rich while the H-atoms are electron-poor. Thus, the electronegative O is attracted to a positive surface while the electropositive H are repelled.

Figure 1.2.2. (a) Experimental observations of the ratios of molecular and activated water (taken as OH and O) on the surface of a nickel catalyst after methane steam reforming indicate that positive fields promote water adsorption while reducing its capacity for activation and vice-versa for the negative field. (b) Density functional theory simulations reveal the reason behind these observations [10].

In a negative field, therefore, H atoms are pulled nearer to and are more likely to interact with the surface, breaking the O-H bond and activating water. In the positive field, they are simply too far away to activate readily. Thus, the presence of an electric field does more than just facilitate the movement of molecules (whether translational or rotational), and indeed can affect the selectivity of reactions by manipulating adsorbate orientations with respect to the catalytic surface.

This directly affects the kinetics of the reaction by changing the probability of viable collisions; or changing the frequency factor of the Arrhenius equation as discussed in Section 1.4. In fact, the reactivity and stability of adsorbates are also affected by direct molecular orbital manipulation, allowing all molecules to be affected by the electric field, not just those with permanent dipole moments.

Section 1.3. Electronic Structure

Electrons, being inherently charged particles, are strongly affected by electric fields. It shouldn’t be surprising that structures composed of electrons (e.g. atomic electron clouds, molecules, bonds, orbitals, etc.) are also substantially affected by electric fields.

The Fermi level of a metal, or the location of the metal’s highest occupied molecular orbital

(HOMO), is determined by the complex electronic interactions occurring within a metal crystal and plays a significant role in its effectiveness as a catalyst [11]. If the Fermi level of a catalyst is lower than the HOMO of the adsorbates, then electrons will flow from the adsorbate to the catalyst.

Electrons are removed from the surface by an adsorbate whose lowest unoccupied molecular orbital (LUMO) is lower in energy than the Fermi level of the metal. Thus, a molecule with electrons to spare will not interact strongly with an electron-rich catalyst surface.

If fields of sufficient strength (on the order of 1.0-10 V/nm) are applied, the molecular orbitals of gas-phase and adsorbate molecules can be significantly distorted [12, 13]. “Squashing” the electron density of a molecule in a particular direction sets up instantaneous dipole moments which affect reactivity—the relative ease with which a molecule can be squashed is reflected by its polarizability. For example, the orbitals of a molecule in a strong negative field will be repulsed by the field creating a region of positivity (exposed nuclei) on the side of the molecule nearest the field source (e.g. the catalyst surface). The negatively charged surface then has a greater propensity for reaction with the now-positive surface of the molecule. In this way, even completely neutral molecules can be affected by electric fields of sufficient strength. In fact this is one of the operating principles behind the field ion microscope (FIM): an extremely high positive electric field is applied to a metal surface so that approaching molecules are first polarized, then attracted by the surface. This application will be discussed in more detail in Chapter 2.

This “squashing” effect can be described more rigorously by examining the energy gained by electrons (therefore atomic and molecular orbitals) within an electric field. Charged particles in an electric field will experience a force proportional to the magnitude of their charge (q) and the strength of the electric field (‖F⃑ ‖). The potential energy (U) gained by the charge is then:

U = q‖F⃑ ‖x (1.3.1) where x is the distance from the “source” of the electric field. To understand this, consider an electron drifting in the uniform electric field between two oppositely charged plates; as the electron moves closer to the positive plate, its electrical potential energy decreases just as the gravitational potential energy of a rock decreases the closer it gets to the surface of the Earth. Unlike the field between these imaginary plates, however, the electric field strength may also be a complex

11 function of distance from the source depending on the source geometry. Some common examples are summarized in Table 1.3.1.

Table 1.3.1. Electric field strength dependence on distance from the source changes according to the geometry of the field source as illustrated by these common examples. Red arrows represent the electric field.

Geometry Electric Field Strength† Eq.

q ⃑ Point charge ‖F‖ = 2 1.3.2 4πε0x

λ Infinite line of charge ‖F⃑ ‖ = 1.3.3 2πε0x

σ Infinite charged plane ‖F⃑ ‖ = 1.3.4 2ε0

σ x ⃑ Disk of charge ‖F‖ = (1 − 2 2 1⁄2) 1.3.5 2πε0 (x + R )

q ⃑ Charged sphere ‖F‖ = 2 1.3.6 4πε0(x + R)

† In these equations, q is total charge of the source, ε0 is the permittivity of free space, x is distance from field source, λ and σ are linear and surface charge densities respectively, and R is the radius of the field source.

At first glance, it seems that the amount of potential energy gained by an orbital in a field will depend heavily on the local geometry of the field source since Equation 1.3.1 depends on field strength, which itself depends on geometry. A simplification can be made, however, by considering the scales involved during catalysis. Molecules adsorbed or approaching a large catalyst particle (on the order of microns) will “see” a large plane tens of thousands of times its own size. To a molecule then, micrometer dimensions may as well be infinite. Additionally, we need only examine the behavior of the field within a few Ångströms of the surface since catalysis occurs near the surface. In this case the catalyst surface can be treated as an infinite charged plane.

Combining Equations 1.3.1 and 1.3.3 indicates that the potential energy gained by a molecule in a field at the surface of a catalyst is:

eσ U = x 1.3.7 2ε0 where q has been replaced by the fundamental charge, e, since the particles in question are electrons. This is a linearly increasing function of distance from the surface and was first used by

Kreuzer to describe the effects of an electric field on adsorbates [13]. The overall effect of electric fields on adsorbate-catalyst interactions is summarized in Figure 1.3.1. It is important to note that

U does not increase infinitely with increasing x, as the catalyst surface ceases to resemble an infinite plane as the reference point withdraws. At sufficient distance, the catalyst appears as a point charge and the energy begins to decrease as a function of distance:

q2 U = 1.3.8 4πε0x

Figure 1.3.1. The application of a positive electric field (F) to a heterogeneous catalytic system causes energy (E) changes in the atomic orbitals (AO) of species A and B resulting in new molecular orbitals (MO) for molecule AB. Interactions between the HOMO/LUMO of AB and the surface can change substantially in the presence of the field.

With very small particles, however, the analysis used here and by Kreuzer may no longer apply. Catalyst particles on the nano-dimension will only be tens of times larger than an individual molecule, so the field may no longer behave as if emitting from an infinite plane. In this case, analysis using a charged sphere (Equation 1.3.6) is probably more representative of reality. The potential energy curve will therefore continually decrease as a function of distance from the surface, rather than increase. This can substantially affect the analysis of an EFAC system since, even though field strength is increased with larger particles, the molecular orbitals may no longer be affected in the same way relative to each other.

It has been hypothesized that electric fields can also shift the Fermi level of a metal, thereby raising or lowering the work function (Φ) [14, 15]. In addition, several groups have shown that work function correlates with reactivity for many systems [16, 17]. Hence, if the work function can be tuned by the application of external fields, this is another means by which reactivity can be tuned in EFAC systems. However, this claim is controversial as the Fermi level is generally considered an emergent property of bulk metals rather than a surface phenomenon. Hence, some

14 disagreement is to be expected regarding the nomenclature used in this discussion. It is undoubtedly true, however, that the surface electronic properties will change after charging a surface or in the presence of high electric fields. Perhaps a more accurate way to describe this phenomenon would be as a shift in the d-band center of the material. That is, the mean orbital energy of the metal electrons is altered. Since d-band structure is fundamentally important to catalytic behavior [18], one might expect that manipulation of the d-band by fields to have a similar effect to manipulating the d-band by changing dopant levels, dopant identity, support structure, support composition, or particle geometry. Several groups have correlated changes in the d-band center with changes in catalytic activity for a variety of catalysts [16, 19-22].

Regardless of which model is used (work function or d-band center), the overall interaction between adsorbates and the surface can be captured by analysis of the energies of adsorption and desorption. This analysis leads to the construction of so-called “volcano” plots and gives rise to the Sabatier principle—the idea that a surface must bind adsorbates strong enough to react them, but not so strongly that the products cannot escape [23, 24]. Examples of these types of relationships are common in catalysis [25-27]. In fact, this general principle underpins most of the traditional “tools” of catalysis. For example, contacting two different materials causes electronic imbalances which alter the electronic structure of both materials. Hence, support-particle interactions, core-shell structures, and dopant effects all work, at least in part, through these shifts in electronic structure. Applying electric fields is the only way to achieve these same surface energetics rearrangements without adding or removing atoms from the catalyst.

Section 1.4. Kinetic and Thermodynamic Changes

Ultimately, engineering any chemical process always requires fundamental knowledge of its thermodynamic and kinetic properties. The topics covered in previous sections lay the groundwork for understanding these important process variables and how they change in the presence of strong electric fields. We now develop the tools necessary to make testable predictions for EFAC processes using the principles outlined in Sections 1.1-1.3.

As already mentioned, electric fields affect heterogeneous catalytic reactions mainly by interaction with the dipole moments (Section 1.2) and the polarizabilities (Section 1.3) of participant species. These two quantities can be used to describe an electrical moment (M) of the molecule: generally, how much force is experienced by a molecule in an electric field (F) due to its permanent dipole moment (μ) and changes in its dipole due to polarization:

1 1 M = μ + αF + βF2 + γF3 + ⋯ 1.4.1 2 6 where α is the polarizability and β and γ are the first and second hyperpolarizabilities, respectively

[28]. These latter two terms are generally quite small and may be neglected [29]. It was shown by

Bergmann et al. in 1963 that the equilibrium of reactions occurring within the influence of strong electric fields will be altered according to a van’t Hoff-like relationship in exactly the same way that changes in other state variables (such as pressure and molar volume) can affect equilibrium:

∂ ln(K) 1 ∆M = (∑ M푝푟표푑푢푐푡푠 − ∑ M푟푒푎푐푡푎푛푡푠) = 1.4.2 ∂F kBT kBT

16 where K is the equilibrium constant, kB is Boltzmann’s constant (use the Universal Gas Constant,

R, for molar changes), and T is the reaction temperature [30-32].1 Integrating Equation 1.4.2 using the boundary condition that the equilibrium constant in the electric field must reduce to the standard equilibrium constant when the field is zero (K|F=0 = K0) yields:

1 1 (∆μF+ ∆αF2) k T 2 1.4.3 K = K0e B

In effect, then, EFAC is another method of introducing energy into a system. This energy input causes shifts in the thermodynamic equilibrium of a reaction analogous to changing the temperature. Because the field term associated with the dipole moment is linear (∆μF), the effect will be different depending on the direction of the applied field. This property allows the user to fine-tune the selectivity and yield of a reactive process by controlling the electric field strength and direction.

Equation 1.4.3 can be used to predict the effects of an electric field on the thermodynamics of simple systems. Formic acid decomposition is a relatively simple process involving only two reaction pathways: dehydrogenation and dehydration. It is therefore an ideal candidate for analysis using this procedure. A detailed analysis is described in Chapter 4, but an example result is provided as Figure 1.4.1a.

1 Several references imply the use of electrical energy in place of the electric moment: ∆M = ∆μF + 0.5∆αF2 + ⋯ . Note that the units of Equation 1.4.2 are inconsistent if this form is used. See Appendix A for a discussion of the correct use of Equation 1.4.2.

Figure 1.4.1. (a) Applying Equation 1.4.3 to real formic acid decomposition selectivity data (“No Field Data”) indicates that formic acid dehydrogenation (CO2 production) should be greatly improved by the presence of a negative field. (b) Considering the formic acid dehydrogenation mechanism using the methods described in Section 1.2 indicates that a negative field should increase the rate of the formic acid dehydrogenation reaction. Thus both thermodynamic and kinetic considerations imply that the negative field is beneficial for formic acid dehydrogenation.

Understanding kinetic changes brought about by the application of an electric field requires the availability of a detailed mechanism. Although some predictions may be made by knowing only a fraction of the total reaction pathways, unexpected changes may occur if all possibilities are not analyzed [9]. For comparison with the thermodynamic calculation, we consider the case of formic acid decomposition. A full mechanism for this process will be developed in Chapter 3, but for now it suffices to consider only the dehydrogenation mechanism shown in Figure 1.4.1b. The rate-limiting step of this process is the scission of one of the O-surface bonds of the bidentate or bridged formate species and rotation into the less-stable monodentate H-down conformation. At this point, C-H bond cleavage occurs rapidly and CO2 and H* are produced. Making this rotation step more favorable will increase the rate of the dehydrogenation reaction.

The blue and red arrows in Figure 1.4.1b represent the dipole moment of surface formate and a negative applied electric field, respectively. The angle between these vectors is 180° (they are antialigned), so although no torque is experienced according to Equation 1.2.1, it now exists in a physically unstable equilibrium. Any rotational movement of the molecule will cause the fragment to rotate into a more physically stable position in an attempt to align the dipole moment

18 and the electric field. Since this rotation puts the molecule into a chemically unstable position, cleavage of the C-H bond rapidly occurs.

Other parameters, such as bond strength with the surface, are not as easily determined using such simple “rules of thumb.” Adsorption and activation energies for the process within an electric field must be computed using the rules of quantum mechanics. This has been done for the species and elementary reactions during methane steam reforming over nickel using ab initio density functional theory computations. The interested reader is referred to the work of Che et al. for details on how this was accomplished [10, 33, 34]. It is useful to write the Arrhenius equation as a function of field strength:

E (F) − a k(F, T) = A(F)e RT 1.4.4 where k is the rate constant, A is the frequency factor (sometimes called the pre-exponential factor in engineering circles), and Ea is the activation energy. In analyzing the configurational stability of the formate fragment with respect to the surface we have determined that the probability of favorable collision should increase—that is, the frequency factor should increase. Although hypothetically a full quantum mechanical study is required to understand the effects of applied fields on bond stability (and therefore activation energy), some educated guesses can be made by charge analysis analogous to predicting acid-base interactions in organic chemistry. For instance, the presence of electronegative O atoms near the surface suggests that increasing the surface negativity will destabilize the O-surface bond, lowering the activation energy barrier for formate decomposition. Thus, we expect both A to increase and Ea to decrease in the negative field so the rate constant for formate rotation should increase. Hence, for this particular step, both the thermodynamics and kinetics agree that negative applied fields are beneficial.

Section 1.5 Intrinsic or Natural Field-Enhanced Catalysis

Although this dissertation focuses on attempts to enhance chemistry with applies electric fields, it can be instructive to examine situations where such enhancement arises naturally. As the science of catalysis in general can be viewed as almost purely electronic phenomenon (promoters and supports affecting catalyst electronic structures, for example), it should not be surprising that some of the most reactive natural catalytic systems appear to function at least partially through electric field enhanced chemistry.

Zeolites are a common catalytic material in many industrial applications useful not only for their size-selective properties as “molecular sieves” but also for their interesting catalytic properties [35]. It has been found that the electric fields inside of zeolite cavities where active metal centers reside can contain electric fields on the order of 1-10 V/nm [36-40]—and 100 V/nm have been suggested by some researchers [41]. Although the true magnitude of these fields is still not known, their presence is acknowledged and used in zeolite catalyst designs [42]. These fields arise from the confinement of ions within the tiny cage-like structures of the zeolite [43].

The confinement of ions in small spaces also occurs in biology where the activity of many enzymes has been connected to the very high electric fields present near the active site [44]. These fields are generally on the order of 1 V/nm and have been discovered in a wide range of enzymes including aldose reductase [45, 46], subtilisin BPN’ [47, 58], ketosteroid isomerase [49], human oncoprotein p21Ras (a small GTPase) [50], and dihydrofolate reductase [51]. Like the high fields present in zeolites, these fields arise from the confinement of charges within small spaces. In the case of enzymes, however, these are not necessarily metal ions but can also include charged

+ - functionals like amino (R-NH3 ) and carboxyl (R-COO ) groups on the protein subunits of the enzyme that are folded into the pocket.

A similar story plays out with sterically hindered or “frustrated” Lewis acid-base pairs

(FLPs), which have also been shown to have high catalytic activity for many reactions [52-54].

Grimme et al. attributed the increase in activity of H2 activation over FLPs to “the polarization of

H2 induced by the electric field of the FLP inside its cavity” [55]. This idea of FLP catalysis by internal electric fields has been challenged by Rokob et al. in a 2013 review, however [56], and work by Yepes et al. found that, although electrostatic interactions within the FLP are important, they are not the strongest contributor to FLP reactivity [57].

High electric fields also arise within the Helmholtz double-layer (HDL) at electrode-liquid interfaces in electrochemical cells. HDLs have been postulated since at least 1861 [58], and computations have been available since at least 1941 indicating field strengths on the order of 1

V/nm within the HDL itself [59]. Stark probe measurements of the field strength within HDLs have been available since at least 1985 [60, 61], and this 1 V/nm strength has since been confirmed by other groups in a variety of systems [62-66]. Hiesgen et al. were able to estimate the field strength at different layers in the HDL using a scanning tunneling microscope and further confirmed these strengths [67]. HDLs form quite naturally around the electrodes in an electrochemical cell as ions are attracted to the electrode surface. Counterions are then attracted to this first layer of ions creating a thin region consisting of two layers of oppositely charged particles.

The proximity of these charged groups leads to an extremely steep potential gradient between the layers: or very strong electric fields. As might be expected, the strength of these fields depend substantially on the applied voltage at the electrode since higher motive forces attract more ions

21 which, in turn, generate higher fields within the layer. Ion size and electrode geometry are also important factors in determining the field strength within the HDL as these factors influence the ion distribution and orientation within the layer [68].

In summary, electric fields can—and do—play an important role in chemical reactions.

This is perhaps not so surprising since atoms and molecules consist of charged particles. However, the phenomenon is scientifically interesting since changes in the dynamics of reactions due to the presence of electric fields can lead to fascinating new chemistry. EFAC is also a potentially exciting reaction engineering tool which may improve reaction rates, decrease energy costs, and increase product yield and selectivity. When designing EFAC systems for any application it is crucial to consider the chemical structure and environment around the reactants as well as the macroscopic electric properties of the system. From an engineering perspective, the latter considerations may tend to dominate but, as observed in nature, the former also plays a substantial role. As the focus of this dissertation is on the design of EFAC systems which do not rely on familiar chemical principles but rather on more general physical principles, an examination of the current state-of-the-art in EFAC engineering—presented in the following chapter—may be beneficial.

CHAPTER 2: PRINCIPLES OF EFAC REACTOR DESIGN

“It should not be surprising if in the future, field ion microscopy reveals some more field-induced chemical reactions since by using this tool we can now control, by the turn of a knob, fields that are equal in magnitude to the ones acting between the ions in chemical compounds.” –Erwin W. Müller, 1960 [1]

This chapter is essentially a more detailed version of a 2018 review published in ACS

Catalysis on electric field-induced catalysis—particularly focusing on expanding the information written in Section 4 of the perspective [2]. We will explore the various methods by which electric field assisted catalysis (EFAC) has been attempted experimentally. Each section highlights a different reactor configuration, its general operating principles, and a review of the work that has been done on each. The scientific and engineering relevance of each system will also be discussed.

We begin with a brief overview of the field emission and field ion microscopes (FE/IMs) in Section 2.1. The historical significance of these instruments cannot be overstated: they are the progenitor of all EFAC studies and the technique has a long and storied history with myriad applications. In the interest of brevity, Section 2.1 focuses only on the key developments and findings of FIM studies that are relevant to the rest of this dissertation.

Subsequent sections are presented in no particular order, except that some attempt is made to keep similar concepts grouped together. Thus, Section 2.2 details the scanning tunneling microscope (STM), the atomically sharp tips of which resemble the FE/IMs. Section 2.3 and 2.4 cover the “probe-bed-probe” style reactors and capacitor reactors—both hopefuls in the push to scale up the field emission/ion microscope observations.

Section 2.5 introduces the integrated circuit reactor (ICR), the primary reactor design investigated in the rest of this dissertation. This design bears little resemblance to those covered in

23 the other sections and relies on electrical physics that many readers may not be familiar with.

Because of this, and the fact that the ICR design is used in the experiments discussed in following chapters, more time and effort will be taken to ensure adequate coverage of the working principles of the ICR.

An attempt is made to consider both the scientific and engineering advantages and disadvantages of each reactor design at the end of its corresponding section. However, it is ultimately left to the reader to evaluate and judge the designs according to their own needs. The scientist wants to perform experiments in the most ideal setting possible, allowing for more control over system variables and to get at the fundamental processes. An engineer, on the other hand, must consider the practical requirements of the reactor: how much material is it able to process per unit time? Is it stable in the long term? Is it safe to operate? Is it a cost-effective solution to a current problem? No single reactor has yet been invented (and, probably, never will be invented) that meets both scientific and engineering requirements completely. For example, although the

ICR meets many of the scalability and flexibility demands of the engineer, it is not a “clean” enough system for the scientist—it runs at high pressure which makes it difficult to compare to quantum mechanical analyses.

Section 2.1. The Field Emission and Field Ion Microscopes

The field emission and field ion microscopes (FE/IMs) are among the most important and influential scientific instruments in modern history. It is with the use of the field ion microscope that the first atomic-resolution images of a metal surface were obtained. The instrument also allowed, for the first time, the study of controlled chemical reactions in extremely high artificially applied electric fields. The instruments have had such a massive impact across a variety of fields

24 of study that it is sometimes difficult to extract the pertinent literature from the irrelevant. For the beginner, the 2018 perspective by Che et al. [2] is an excellent starting point for the basic principles of operation and a review of studies relevant to field-induced chemistry. Two reviews written for a general audience by Müller himself are also highly recommended. These are a 1961 paper written for American Scientist which covers the basic principles of FE/IM, its development, and its implications for the field of microscopy in general [3]; and a review of the techniques and principles of operation for Science in 1965 [4].

A detailed account of the history of FE/IM development was published by Drechsler in

1978; this provides additional background information that is generally unavailable in the scientific literature including the impetus for the development, highlights of some frustrating or disappointing moments along the way that eventually led to further improvements, and the impacts of the uncontrollable chaos of worldly events on Müller’s work (e.g. the second World War) [5].

More technically detailed accounts of the history of development of FE/IM and its operating principles were written by Müller and Tien Tzou Tsong in 1969. This book is an excellent read for any researcher interested in this area and includes detailed schematics of early instruments as they developed as well as the mathematical underpinnings and reasoning behind the technique [6]. Books by Bowkett and Smith [7]; Wagner [8]; and Sakurai, Sakai, and Pickering

[9] are also worth reading.

We will be drawing from all of these sources and more in the discussions to follow. Due to the historical significance of FE/IM on EFAC, we will touch briefly on the history of the instrument’s development in Section 2.1.1. This treatment will not be given to the other techniques discussed in subsequent sections. The rest of Section 2.1.1 is devoted to outlining the basic

25 principles of operation of FE/IMs. Relevant studies and their connection to the work presented in the rest of this dissertation are summarized in Section 2.1.2. A few points on the practicality of

FE/IM from an engineering perspective are presented in Section 2.1.3.

Section 2.1.1. Principles of Operation

The first field emission microscope (FEM) was created by Erwin W. Müller in an attempt to solve a mystery with his Ph.D. dissertation work on field emission from surfaces [5]. This prototypical FEM consisted of a 1 L glass bulb covered with a fluorescent willemite (Zn2SiO4) screen and silver coating to prevent charging. A piece of fine tungsten wire was used as the emitter.

Images obtained in this manner were, at first, not particularly useful as they fluctuated rapidly and did not appear to show anything definite [10, 11]. However, the groundwork was laid for rapid advancements in the coming decades—from Müller himself as well as a large host of other researchers. Improvements to the FEM design, also by Müller, were published in 1951 under the title “Das Feldionenmikroskop” or the field ion microscope (FIM) [12].

Both FEM and FIM are similar in operating principle with only a few key points of difference. FE/IMs consist of a very sharp metal probe subjected to high voltages (on the order of

103 V) to generate electric fields as high as 1010 V/m. The surrounding apparatus allows for the collection of images of the surface at atomic resolution, and, later, the detection of chemical species emitted from the surface by mass spectroscopy [13]. Collecting the mass spectrum of gases during

FE/IM operation has been called “Atom-Probe Field Ion Microscopy,” but this distinction is not used in the following discussion. General schematics of the instrument are provided as Figure

2.1.1.1. The key differences in operation between FEM and FIM are the electrical bias used and the atmosphere surrounding the sharp metal tip.

Figure 2.1.1.1. (a) Müller’s original FEM prototype schematic, reported in Zeitschrift für technische Physik in 1936 [11]. Simplified schematics of (b) the construction and (c) principles of operation of the FIM. Red arrows represent field lines, dotted black arrows represent the path of motion of reactant (oval) and product (circle) molecules. The products, being positively charged from interacting with the tip, are ejected from the tip along a field line due to electrostatic repulsions.

In general, FEM probes are subjected to a negative bias, meaning the surface of the sharp metal tip is negatively charged. Electrons then tunnel out of the sample (generally a fine wire or sharp metal tip) and are attracted to an imaging plate maintained at a positive bias. Images of the surface of the emitter can thus be obtained. To prevent deflection of imaging electrons and blurring of the image the FEM is operated under high vacuum.

FIM, on the other hand, is operated with the probe under positive bias. Thus, no electron emission is observed. Instead, the probe surface is bombarded with an imaging gas such as He.

Quantum tunneling of image-gas electrons into the metal probe surface produces cations that are subsequently strongly repelled away from the charged surface. These ions impinge upon an imaging plate (or are directed into a mass spectrometer through a small hole), allowing for high- resolution imaging of the surface. Not only sharp needle tips, but thin wires and sharp metal edges have been successfully imaged using FIM [14]. The first images of metal surfaces with atomic- scale resolution were taken using FIM, and the technique has greatly advanced our understanding

27 of surface science in general and catalyst structures in particular. One example of such imaging on modern instruments is provided in Figure 2.1.1.2.

Figure 2.1.1.2. (a) An image taken of a Pt sample on a modern field ion microscope compared to (b) a ball model of a face- centered-cubic hemispherical crystal. Miller index planes are shown. Bright spots in both images correspond to locations of high activity, generally corresponding to protruding atoms where the electric field is highest, e.g. kinks and steps. Taken from Che, et al. [2].

Moreover, if the FIM is operated in atom-probe mode (i.e. with a mass spectrometer attached), the products of chemical reactions at the probe surface can also be measured. This technique kicked off the study of chemical reactions in extremely high electric fields. Several examples of these kinds of studies are examined more closely in Section 2.1.2.

Section 2.1.2. Relevance to Current Work

Studies of field-induced chemistry using FIM started as early as the 1960s and have continued at least to the time of writing. Most FIM studies use a “pulsed field” technique that does not use consistently applied fields, so their connection to the work discussed in later sections is somewhat limited, though pulsed fields are investigated more in Chapter 6.

John R. Hiskes performed the first quantum mechanical computations of molecular dissociation in extremely high electric fields on the order of those produced in a FIM in 1961 [15].

+ These computations were performed for the hydrogen ion (H2 ; H2 was used as an imaging gas in the first successful FIM images) and other simple two-atom molecules including HD+ and LiH2+.

This work demonstrated the theoretical ability of simple molecules to dissociate in electric fields on the order of 0.1 V/nm for the first time and laid the groundwork for future computational advancements in this area.

Some of the earliest work conducted with FIM for field-induced chemistry was reported in

1965 by Lorquet and Hall and involved both computational and experimental investigations into the ionization and breakdown of straight-chain alkanes in very high electric fields [16]. This work is foundational because it attempted, for the first time, to connect the chemical reactivity of molecules to electric field strength at the probe tip; an idea that has been expanded upon in the present work, as discussed in Chapter 4. Although the researchers were unable to determine the field strength precisely at the active site (a problem which persists to this day), they were able to broadly determine the threshold field strength at which field-induced chemistry becomes significant. For n-heptane, for example, this threshold field was determined to be ~6 V/nm [17].

The chemical changes observed experimentally were attributed to molecular reconfiguration (e.g. from a linear configuration to a bent one) as well as distortion of the molecular orbitals of the molecule. It’s important to note that, being nonpolar molecules, alkanes are only affected by electric fields through polarization of their electron clouds, and therefore require significantly higher field strengths than a molecule with a permanent dipole moment might to be significantly affected by the field.

Röllgen and Beckey were the first to consider condensed multilayers on an FIM tip for reactive systems in 1973 [18]. This work, while not conducted with catalytic FIM tips, represents the first time that reactive systems reminiscent of a “high pressure” type system (condensed layers on the surface) were investigated. It was found that the primary effects of an electric field on non-

29 catalyzed reactive systems was the facilitation of proton transfer reactions. Particularly interesting is that these proton transfer processes were observed with a variety of types of molecules: not just alcohols and ketones, but even with hydrocarbons. Methane, for example, was observed to form

+ CH5 ions in the presence of strong electric fields via a proton-transfer reaction:

2 CH4 ⟶ CH3• + CH5+ + e- 2.1.2.1

Hence, although the focus of this dissertation is on catalyzed reactions in an applied field, the effects of gas-phase or even non-catalyzed surface reactions cannot be ignored. Some observed phenomena incongruent with those predicted from computational analysis of catalytic systems in electric fields may be attributable to unexpected side-reactions like this.

The first rigorous investigations into field-induced chemistry of multi-atom polar molecules using an FIM were conducted 1974 and 1975 using aldehydes (specifically propanal

[19] and ethanal [20]). However, these investigations were solely computational and sought to understand the configurational changes of polar molecules in high fields rather than reactivity.

This work found that extremely high fields at a metallic interface can cause significant rearrangement in the structure of polar molecules, a concept that is relied upon later in this dissertation to influence the reactivity of formic acid (see Chapter 4).

Cocke et al. and McEwen et al. in 1995 and 2008, respectively, investigated the oxidation of metal surfaces in high electric fields using pulsed field desorption mass spectrometry (PFDMS), a specialized form of FIM which couples pulsing electric fields in a FIM and mass spectrometry.

Cocke et al. used Cu oxidation to show that the migration of ions and defects near the surface and at oxide-metal interfaces is greatly enhanced in the presence of high positive field pulses [21].

McEwen et al. showed that the oxidation of Rh metal is greatly enhanced in an external field [22].

The latter study was also demonstrated from first-principles using density functional theory analysis. Both studies are important for understanding the complex nature of field-induced chemistry: not only are the reactive molecules impinging the surface affected, but the surface itself is altered through rearrangement of defects and migration of ions into and out of the bulk phase.

This phenomenon is also observed in the work reported in Chapter 5 of this dissertation.

One final set of representational FIM studies that are relevant to the work presented in this dissertation are the 1987-1989 papers on methanol decomposition from the Fritz-Haber Institute.

These studies, conducted using PFDMS at a range of steady field strengths, found that methanol was strongly affected by electric fields above 2.0 V/nm. Chuah et al. found that adsorbed methyl groups on a Ru surface are stabilized by a positive electric field [23]. This finding corresponds well with observations made by the work presented in Chapter 5. Kruse et al. found that the rate of methanol decomposition was decreased in a steady electric field and that its decomposition intermediates were similarly stabilized [24]. This finding corresponds with work discussed in

Section 2.5.2 which suggested that methanol production may be enhanced in an applied field within an integrated circuit reactor. Two final important observations were made by Chuah et al. during methanol decomposition over Rh: (i) reaction equilibrium is shifted in a new direction not observed in the no-field reaction scenario, producing aldehyde functionals and (ii) specific orientations of intermediate fragments are favored in the presence of a field, particularly the upright configuration of CH2O* fragments [25]. Compare these observations to the discussion of kinetics and thermodynamics in high fields presented in Section 1.4.

The work presented in the rest of this dissertation owes a huge debt to the FE/IM and those who pioneered the field. Without this foundational work, our understanding of field-induced

31 chemistry (to say nothing of EFAC!) would be severely lacking. That said, there are a few issues that must be addressed with FE/IM in regards to its practicality.

Section 2.1.3. Practical Considerations of FE/IM

Although FE/IM is an extremely powerful scientific tool for many purposes including but not limited to crystallography, catalysis, and field-induced chemistry, it is not a particularly useful tool for the chemical engineer interested in expanding theory into practical commercial or industrial applications. To the scientist, of course, there is nothing better. The technique is supremely suited to comparison with computation because it tends to operate under high vacuum over extremely ideal metal surfaces polished by field evaporation. These conditions closely approximate (as nearly as currently possible) those scenarios constructed by the most sophisticated of density functional theory models where a handful of molecules (at most) are simulated reacting on an idealized surface in vacuo.

Of course, from an engineering perspective nothing could be so impractical. For a start, the pressures used in FE/IM are nowhere near what would constitute a realistic reactor. For example, a typical FIM experiment might be conducted under high vacuum at ~10-4 Pa. Typical engineering applications call for pressures much greater than atmospheric (105 Pa), which is already nine orders of magnitude higher than the pressures within an FIM! How such a large increase in pressure affects the behavior of electric field assisted chemical systems is an interesting question. The chief concern with applying fields on the order of 1.0 V/nm in a high-pressure system is dielectric breakdown or plasma formation. This is most certainly the immediate outcome of a pressurized

FIM experiment. As will be discussed in more detail in Section 2.3.2, such an outcome is undesirable from both an engineering and scientific perspective.

Section 2.2. The Scanning Tunneling Microscope

Like the field ion microscope, scanning tunneling microscopes (STM) are nearly ideal electric field reactors for comparison to computational models. Their atomically sharp tips allow for the easy creation of >10 V/nm electric fields and for the analysis of single molecules or a handful of molecules. Aside from the loss of realism that single-molecule analysis creates (due to lack of lateral interactions, side reactions, and so forth), the reactants must be chemically bonded to the STM tip during analysis. This severely limits the number of possible reactions that can be analyzed in an STM. At the time of writing, only a handful of “field induced chemistry” studies have been conducted using STM, none of which can be appropriately deemed an “EFAC” study since the reactions analyzed were non-catalytic. Because the phenomena involved are tied directly to those that occur in EFAC, however, the STM studies will be briefly discussed here before continuing to other EFAC reactors in the following sections. We begin in Section 2.2.1 with a short discussion of the operating principles of STM with a particular focus on the method by which

STM electric field induced chemistry studies are performed. Section 2.2.2 highlights the field- induced chemistry studies that have been conducted using STM and their significance to the rest of the research presented in this dissertation. Finally, we finish with a few brief notes on the scientific and engineering perspectives on the use of STM for EFAC studies.

Section 2.2.1. Operating Principles of STM

The STM is an instrument that, much like the FE/IM, was developed for the high magnification imaging of surfaces. Like the FEM, the STM relies on electrons emitted from extremely fine or sharp metal tips for imaging. Unlike the FE/IM, however, the STM is used primarily to image a surface other than the tip. Whereas in FIM, images of the metal tip itself are obtained, the STM collects information about a secondary surface brought into contact with the

33 metal tip. In one sense, an STM operates in much the same way as an atomic force microscope

(AFM) which uses a fine metal tip in close proximity to a surface to image the surface itself. Other than this basic similarity, the AFM and STM rely on completely different physical principles.

The STM uses a very fine or sharp metal probe which is brought into close proximity with a surface—typically less than 1 nm. A high electrical bias is established between the tip and the substrate over which the tip moves. An electrical current is then developed, generally on the order of nanoamperes, as a function of distance to the surface, voltage applied, and material type. This current arises due to quantum tunneling of the electrons in the tip passing through the energy barrier of the tip/surface gap and into the surface. As the tip is moved across the surface the magnitude of the current changes as it passes over surface features, defects, holes, etc. This current is readily measured and correlated to changes in height that can then be used to generate images of the surface.

Operating the STM for the purposes of electric field induced chemistry is slightly more difficult. In the first place, the molecules being studied typically have to be bonded to the tip, the substrate, or both. In the case of the Aragonès et al. study that will be discussed in more detail in

Section 2.2.2, a Diels-Alder reaction was examined. The diene was bonded to the STM tip (in this case, made of gold) while the dienophile was bonded to the substrate (also gold). To accomplish this, however, sulfur groups had to be added to the molecules in order to get them to bind to the gold in the orientations required. It is very likely that the addition of these extra functional groups had some effect on the molecule that it would not otherwise be afflicted by in a free-mixing reaction (e.g. aqueous or gas phase). If the molecule is large enough, and the substituent added far enough away from the reactive sites, it may have a negligible effect. However, the analysis of

34 many important reactions involving gas-phase molecules (e.g. methane) may not be possible accurately in an STM for this reason. A general schematic of STM operation for field-induced chemistry studies in provided as Figure 2.2.1.1.

Figure 2.2.1.1. Schematic representation of the STM for use in field-induced chemistry studies. This representation may not reflect all studies accurately. Red arrows indicate field lines, R and R’ are reactant molecules bonded to the STM tip or substrate surfaces.

Section 2.2.2. Relevant Studies

Only a handful of STM studies have been conducted which explicitly analyze the connection between the electric field and chemical reactivity.

The earliest known study on the effects of an electric field using an STM was conducted by Persson and Avouris in 1995 [26]. This work used a computational modelling approach to investigate the effects of fields on the order of 1-5 V/nm on chemical bonds in an STM. The authors found that bonds could be weakened or strengthened in the field depending on a number of factors including the orientation of the field and the inherent strength of the bond (i.e. the relative energies of the bond orbitals).

Aragonès et al. used an STM with a gold tip to analyze the Diels-Alder reaction between

1-methyl-2-thiol-furan (the diene) and tricyclo[4.2.1.02,5]non-7-ene-3,4-dimethanethiol (the

35 dienophile) [27]. The diene was bound to the gold STM tip and the dienophile was bound to a gold substrate, both through their thiol groups. An electric field was then applied through the tip using a potential of just a few volts and analyzed the reaction rate by measuring the current through the tip. It was found that the frequency of diene-dienophile binding events (measured as current blink frequency) increased by as much as 5 times in a positive field (measured with respect to the tip).

A negative field, on the other hand, showed no increase in blinking frequency. The authors also modeled this reaction using Gaussian-04 and attributed the increase in reaction frequency to the stabilization of resonance hybrids in the electric field. Additional structural analysis presented in their Supplementary Information also suggests that molecular orientation played a significant role in this effect. Diels-Alder reactions are highly orientation-specific, with a range of possible products depending on how the diene and dienophile approach one another. Realistically, both effects likely played a role in these experiments, however neither orbital reconfiguration

(resonance hybrid stabilization) nor conformational changes were confirmed experimentally. This work inspired a thorough perspective on electric fields as “smart reagents” by Shaik, Mandal, and

Ramanan in 2016 [28]. This perspective focuses on the influences of electric fields on molecules from a quantum mechanical perspective and is recommended for the interested reader.

In another STM study, Alemani et al. examined the isomerization of azobenzene in an electric field—demonstrating the effects of electric fields on molecular orientation and configuration [29]. Azobenzene molecules were bonded to the substrate and a high electric field was applied using an STM tip that was also used to measure the conformation of the molecules before and after exposure to the field. It was found that the molecules tended to rearrange from the trans to the cis conformers in the presence of an electric field. This isomerization phenomenon was observed even when the STM tip was withdrawn to such a distance that no tunneling current

36 occurred. It was concluded that the presence of an electric field alone is enough to induce the isomerization of molecules.

No further studies examining field-induced chemistry using STM are known at the time of writing.

Whether this is because of the difficulty in conducting such a test or because the technique is still in its early stages is not known.

Section 2.2.3. Practical Considerations of STM

Much like the FE/IM, the STM is excellently suited for comparison with computational models. Single crystal or oriented crystal substrates can be used that closely resemble the surfaces used in modelling; the measurement chamber is generally maintained at high vacuum; and only one to a handful of molecules at a time are measured. Thus, the same practical considerations that applied to the FE/IM also apply to the STM, particularly with regards to the scalability of the instrument. It is simply not ever going to be used as a practical reactor.

However, unlike the FE/IM, there is an argument to be made for the impracticality of its use as a scientific tool, as well—at least, as far as field-induced chemistry goes. As was discussed in Section 2.2.1, the study of field-induced chemistry using STM requires that molecules are bonded in some way to the surface. In the case of the isomerization study by Alemani et al. discussed in Section 2.2.2, this involved producing a thin film of the material without altering the chemical structure of the molecules in any way. In the case of the Aragonès et al. Diels-Alder study, however, this requires augmenting the molecules with thiol groups. How this addition changes the chemistry and structure of the molecules, and therefore its interaction with the field compared to the non-augmented structure, is unknown. Would the results be any different had these changes not been made? Due to the size of the structures involved, and their remoteness from

37 the active sites, it seems plausible that there would not be much difference in the observed phenomenon. For the study of the small molecules involved in much catalytic research (methane, hydrogen, carbon monoxide and dioxide, etc.) STM seems useless. At least, there is no clear method at this time by which the analysis of small molecules using the STM can be undertaken. It is for this reason that we expect all future studies of field-induced chemistry with the STM to be conducted on rather large molecules. As with all the other techniques in this chapter, however, it is left to the reader to decide how practical any given application may be used for their own work.

Section 2.3. The Probe-bed-probe Reactor

The most extensively studied EFAC reactor system is the probe-bed-probe reactor (PBPR).

Although the operating principles of the PBPR are simple to understand, its actual operation is not straightforward. The chief difficulty in using a PBPR system is in avoiding dielectric breakdown of the reactive gas between the electrodes—that is, arcs or plasma discharges must not occur.

Plasma reactors and reformers are not inherently bad (they are a fairly well-established scientific field in their own right), but they are not fundamentally EFAC phenomena and therefore do not correlate directly with the work discussed in this dissertation. Nevertheless, since there is some confusion in the literature about the method of operation of these reactors, they will be discussed in detail here in the interest of completeness. Furthermore, understanding the physics of dielectric breakdown is important in creating designs which do not suffer from this problem. Section 2.3.1 will outline the general ideal operating principles and design considerations of a PBPR, with an analysis of the actual physics of PBPR operation provided in Section 2.3.2. Finally, the practical concerns of PBPR use for both scientific and engineering applications is summarized in Section

2.3.3.

Section 2.3.1. Principles of Operation of PBPR

In essence, the PBPR operates like a FI/EM except that it is maintained at higher pressures

(usually ~1 atm) and contains a catalyst bed. They generally consist of a tube reactor (often quartz) into which are inserted metallic probes (stainless steel) at some distance from one another (reported as the “gap distance” or “electrode gap”). A wide variety of catalyst materials can be inserted in between the probes. Because the bed does not need to be conductive, this can consist of practically anything. Metal particles supported on alumina, silica, or ceria—introduced as a powder—are common in PBPR studies. Reactant gases are then passed over the bed while a high voltage is applied between the probes. A typical PBPR is depicted schematically in Figure 2.3.1.1.

Figure 2.3.1.1. A schematic representation of a probe-bed-probe reactor. The blue cylinder represents the catalyst bed which may or may not be the same size as the “gap distance,” or the distance between the probes. Reactant (R) flows through the tube and reacts over the bed, transforming to product (P) which is typically analyzed using gas chromatography. Red arrows represent field lines and the black dotted arrow represents the path of a molecule through the reactor.

Most PBPR studies are conducted under constant current conditions. This means that the researcher sets their power source to a constant current value (e.g. 3 mA) and the power box supplies just enough voltage to generate that current. This impressed voltage can be anywhere from 101 to 103 V. Astute readers will be wondering how the current is able to flow between the two disconnected probes. Indeed, since the PBPR is not a closed circuit, no current should be possible between the two probes. However, as will be discussed more in Section 2.3.2, the high pressure conditions used in the PBPR make it extremely likely that, under these very high electric field conditions, ionization of the gas readily occurs which creates current-carrying species. While this is acknowledged explicitly in the early PBPR literature, it seems to have been omitted or overlooked in recent years. Recent PBPR literature only claims the effects of an electric field, and does not acknowledge the competing effects that the ionization of the gas stream may have. For this reason, the PBPR literature is presented in some detail in the following section, as a cursory search for “catalysis in electric fields” literature will often return a wealth of these types of studies, and the unwary reader may not consider this issue in detail.

Section 2.3.2. Relevant Literature

The vast majority of PBPR data comes from a research group in Japan. Because one particular name seems to be common among them (generally as the PI, though in early literature as first or second author), this group will be referred to as the Sekine group unless a specific paper or author is made reference to. On the whole, the Sekine group has been extremely prolific, generating some 37 papers using PBPRs in the past 19 years with an alarming spike in publications on the topic in the last three years as shown in Figure 2.3.2.1. This work, summarized in Table

2.3.2.1, covers a wide range of chemical reactions, catalysts, temperature conditions, and so on.

Interestingly, the phenomenon used to explain the observations also changes despite reactor

40 configuration and other methodological details remaining unchanged. While evolving explanations and hypotheses are expected on the frontiers of science, the Sekine group work is interesting because it appears to be moving further away from the truth with each subsequent publication. To explain how, we must explore the physics proposed in the early Sekine work (2008 and earlier): direct current pulsed discharge, corona discharges, sparks, or, more simply: plasmas.

40 New 9 35 Cumulative 5 30 4 25 2 1 20 2 1 1 15 2 1 2 10 3 4 5 TotalNumber Publications of 1 1 0

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 Year

Figure 2.3.2.1. Sekine group publications using the PBPR configuration in the last two decades. Numbers outside of columns indicate the total number of PBPR publications released in that year (i.e. red portion of bar).

Table 2.3.2.1. Summary of Sekine group work on PBPRs from 1999 to 2018.a Gap Distance Furnace Current Voltage [Ref.] Reactionb Catalyst Physicsc (mm) Temp. (K) (mA) (kV) [30] 1.5 ambient 4 6.25 OCM none DCPD [31] 1.5, 10 453 3 1.07-8.0c MSR none DCPD [32] 1.5, 10 300-773 2.0-4.0 1.8-4.2 DDCM none DCPD [33] 1.5, 2.0, 10 ambient 0.5-8.0 0.3-7.4 OCM Pt/SiO2, Ni/C CD, DCPD [34] 1.5, 5.0 ambient 1.0, 2.0 NR OCM, DDCM none DCPD [35] 1.5, 10 ambient 2.0-4.0 1.8-4.2 POxM none CD, DCPD [36] 5.0 420-800 20000 5.0 DDCM none CD, SD MSR, DDCM, [37] 5.0 420-960 NR NR Lindlar, Ni/C CD, SD OCM [38] 2.1 393 NR NR MSR none DCPD [39] NRe ambient NR NR EtOH-SR none DCPD [40] 6.0e ambient 2.0-15 4-7 EtOH-SR none DCPD Pt on CeO , ZrO , [41] NR 423-623 2.0-3.0 NR Dec. EtOH 2 2 DCPD TiO2 MgO, ZrO , TiO , [42] 6.0 ambient 2 4-10 OM 2 2 DCPD CeO2 [43] 3.0-5.0 425-700 3.0-8.0 0.15 Dec. EtOH Pt/CeO2 EF, DkC EtOH-SR, Dec. [44] 5 423-523 3 0.13-0.60 EtOH, WGS, Pd, Pt, Rh on CeO2 EF MSR d [45] 5 423-753 3 0.46-0.77 MSR Pt, Rh, Pd, Ni on CeO2 EF, DkC [46] NR 423 3 0.9-3.2 OCM La2O3, Sr-La2O3 EF, DCPD f [47] 10-60 423-1650 1-9 0.4-2.0 OCM Sr-La2O3 EF, DkC [48] NR 423 3.0-7.0 0.6-2.3 OCM La-ZrO2 EF [48] 3.0-6.5 423 3.0 0.43-1.16 MSR Pt-CeO2 EF [49] NR 423-723 3.0-7.0 0.87-1.65 Rev. WGS metals on La-ZrO2 EF [50] 1.1 423 5 NR MSR Pd-CeO2 EF [51] 3.2 423-873 3.0-13 0.1-0.9 WGS Pt/La-ZrO2 EF g [52] bed 423 3, 5, 7 0.2-1.3 OCM Ce2(WO4)3/CeO2 EF g [53] bed 473-623 6 0.18-0.23 AS CsRu/SrZrO3 EF g d [54] bed 423 3-12 0.4-2.7 DRM La-Ni/ZrO2 EF g [55] bed 423-633 2-9 1.2-2.5 OCM Ca-La/AlO3 EF [56] 10e 1573 0-9 0.01 PP none EF Ni-Mg on MgO, [57] bedg 473 3 0.1-1.37d TRM EF CexZryO2, LaxZryO2, [58] 4 473-823 5 0.027-0.259 MSR Pd/CeO2 EF e [59] 2.5 623 5 0.071-0.640 Dec. H2O Ce0.62Cr0.33Pd0.05O2 EF [60] NR 473-623 1-6 0.18-0.80 AS Cs-Ru/SrZrO3 EF g [61] bed 423 1.5-7 0.2-1.7 OCM, ODE Ce2(WO4)3/CeO2 EF g [62] bed 423 3 0.4-0.8 OCM Ce2(WO4)3/CeO2 EF [63] NR 473-773 6 0.19-0.61 AS Co/Ce0.5Zr0.5O2 EF g [64] bed 423-673 3-10 0.076-0.196 SRDE Pd/CeO2 EF [65] NR 373 6 0.2 AS Ru/CeO2 EF g [66] bed 473 3 NR TRM Ni-Mg/La0.1Zr0.9O2-x EF a NR: not reported. b OCM: oxidative coupling of methane; MSR: methane steam reforming; DDCM: direct dehydrogenative coupling of methane; MC: methane cracking; POxM: partial oxidation of methane; ErOH-SR: steam reforming of ethanol; Dec. EtOH: decomposition of ethanol; OM: oxidation of methane; (Rev.) WGS: (reverse) water-gas shift; AS: ammonia synthesis; DRM: dry reforming of methane; PP: pyrolysis of propylene; TRM: tri-reforming of methane; ODE: oxidative dehydrogenation of ethane; Dec. H2O: decomposition of water; SRDE: steam reforming of dimethyl ether. c DCPD = direct current pulsed discharge, CD = corona discharge, SD = spark discharge, EF = electric field, DkC = dark current. d Calculated from reported power values (P = IV) e Electrode geometry varies slightly from standard PBPR model, but functions similarly. f Calculated from “effective contact time (ECT)” value given in report. ECT = (gap (mm)/feed rate (mmol/min)). g Probe gap not explicitly reported, but described as resting on either side of the catalyst bed or “contiguous” with the bed.

Section 2.3.2.1. A Brief Overview of DC Discharge Plasmas Plasma, sometimes called “the fourth state of matter,” consists of free-roaming ions and electrons. Common everyday examples include lightning, the sun, neon signs, and sparks. Plasmas are used industrially for welding, etching, nanofabrication, and for waste and pollution treatment.

Although, the details of plasma formation and physics are far outside the scope of this dissertation, the general physics of plasmas will be important to understand for the work conducted in later chapters. In particular, we wish to avoid the production of plasma when exploring EFAC. The purpose of the overviews provided in this and the following subsections are to convince the reader of the fact of plasma formation in a typical DC-operated PBPR as well as how and why it forms.

This discussion will be largely superficial, however important references containing detailed analyses are provided for the interest of dedicated readers.

Plasmas consist of free ions and electrons. They are typically formed when a gas or a liquid

(the focus here is on gases) is subjected to an electric field of such an extreme strength that the electrons are stripped from their corresponding nuclei. This occurs chiefly due to bombardment of the atoms or molecules in the gas by electrons that are accelerated to very high velocities in the presence of strong electric fields (“hot electrons”). These electrons are initially produced by emission from the electrode tip from electric or thermal excitation, or already exist due to cosmic background radiation. The plasma becomes self-sustaining and ignites once the electrons, stripped from atoms via bombardment, are accelerated and can themselves further ionize other molecules.

It is therefore much easier to produce a plasma at high gas pressures, and they are much more difficult to control. The fundamentals of plasma physics are easy enough to find in any undergraduate physics textbook or online, but the following books are excellent detailed overviews: “The Glow Discharge and an Introduction to Plasma Physics” by Llewellyn-Jones

[67]; “An Introduction to Gas Discharges,” by Howatson [68]; “Physics and Applications of

Complex Plasmas” by Vladimirov, Ostrikov, and Samarian [69]; and “Plasma Chemistry and

Catalysis in Gases and Liquids” by Parvulescu, Magureanu, and Lukes [70].

Typical plasmas are produced by controlling the electric current flowing between the electrodes, and not the electric potential. Indeed, the electric potential varies in response to the current applied, not the other way around. This is because the resistance of the gas changes as it is increasingly broken down, so the required potentials to pass a given current through the medium are not necessarily linear. A typical response curve for two electrodes in a low-pressure gas (this is a similar geometry, though not similar atmospheric parameters to the PBPR) is provided as

Figure 2.3.2.1.1. It is important to note that the current values provided here are general and can shift slightly depending on the gas (e.g. the normal glow discharge regime is shown between 10-5 and 10-3 A in some references). Several types of plasma can be identified in such a curve. At very low currents, the plasma is fairly weak and not self-sustaining. This is known as Townsend discharge or, sometimes, a dark discharge (because no light is produced). The Townsend discharge generally forms below 10-5 A (10 μA).

After increasing the current to around 10-3 A (1 mA), the plasma becomes self-sustained and the voltage between the electrodes decreases. This plasma emits a soft glow whose characteristics depend on the type of gas, pressure, electrode geometry, electrode gap distance, and current applied. This plasma is known as a glow or normal glow discharge. Because of the large number of variables involved in characterizing a glow discharge, no succinct method of describing or categorizing them has yet been developed. In general, however, they can be classified by the gas temperature, the electron temperature, and the overall degree of ionization. Glow discharges

generally have similar structures, including dark spaces and glowing regions as shown in Figure

2.3.2.1.1.b. This structure is reproducible across many different gas types, though the distinctions between the zones are lost at the higher pressures used in a PBPR.

Finally, although there are several transitionary regions which are not discussed here, once the current is increased to around 10-1 A (100 mA) and higher, the gas begins to rapidly break down. The potential difference between the electrodes drops dramatically as the electrical conductivity between them rises (due to the presence of large numbers of ions), and a spark or arc discharge is produced. The measured electric potential across the electrodes during arc discharge is often less than 50 V, and the arc itself tends to have a very high gas temperature.

Figure 2.3.2.1.1. (a) General schematic of a plasma generating system (e.g. a Crookes tube) and the (b) corresponding glow discharge profiles generated in tubes of different lengths otherwise using the same parameters. Note that only the positive column changes in length with changing tube dimensions. (c) Breakdown curve for a rarified gas in an electrode- containing tube. Vb is the breakdown voltage, Vn is the normal cathode potential fall, and Vd is the arc discharge voltage. Each of these values will depend on the type and pressure of the gas, the type and distance of the electrodes, and other factors.

There are many other kinds of plasma that can be produced by using different electrical sources (DC vs AC vs radio/microwave radiation), electrode configurations, gas pressures, and so on. The 2002 review by Bogaerts et al. [71] describes these varied phenomena in detail including

DC glow discharges; capacitively coupled radio-frequency discharges; pulsed glow discharges;

atmospheric pressure glow discharges; dielectric barrier discharges; corona discharges; magnetron discharges; low-pressure, high-density plasmas; electron cyclotron resonance sources; helicon sources; helical resonator sources; inductively coupled plasmas; microwave induced plasmas; resonant cavity plamas; free expanding atmospheric plasma torches; capacitive microwave plamas; microstrip plasmas; surface wave discharges; the expanding plasma jet; dusty plasmas; and electron-beam-produced plasmas. Clearly, the majority of these are well outside the scope of the present dissertation. The two in bold (dielectric barrier discharges and dusty plasmas), however, bear some significance to the discussion of PBPRs and will be briefly discussed in the next section.

Section 2.3.2.2. Dusty Plasmas and Dielectric Barrier Discharges Although DC discharges in a rarified gas such as a Crooks tube are a good place to begin in understanding plasma phenomena, they are not obviously representative of the type of work conducted by the Sekine group. Between the electrodes of the Sekine group reactors is, generally, a bed of nonconductive particles some several millimeters deep. The effect this has on the dynamics of plasma formation cannot be understated—plasma dynamics across solid dielectric materials in a gas are completely different from those in a pure gas. To understand how, we will examine two well-characterized extremes of dielectric-plasma interaction: small amounts of dielectrics in the form of dusty plasma and dense dielectrics in the form of dielectric barrier discharge (DBD).

In essence, a dusty (or dirty) plasma is a plasma that has formed in a region of space containing small particles—i.e., a plasma occurring within a colloidal suspension. These particles can consist of anything from dust to metal powder, but insulating materials are of particular interest here as most of the supports used in the Sekine group work are electrical insulators. Dusty plasmas

are important in meteorology and astronomy as both deal with dirty, real-world systems. They are also of interest in microfabrication since plasmas are used for the production of electronics and the presence of dust drastically changes the behavior of the plasma. Hence, dusty plasmas are a fairly well-studied phenomenon. Much of the physics literature appears to focus on the motion of the dust particles—influenced by gravitational and electromagnetic forces, among others—but it is also known how the presence of particles influences the plasma itself.

When a particle is placed within a plasma, it typically accumulates a charge [72]. Such charging tends to be negative due to the much greater relative speed of electrons in the plasma compared to heavier ions. After charging, the particle exerts an electrostatic force on the surrounding plasma, significantly changing its behavior. Charged particles in the vicinity will experience an acceleration due to this electrostatic force which has the effect of increasing the effective electron temperature of the plasma and also changing preferred ion pathways near the particle as shown in Figure 2.3.2.2.1. In some cases, the strong attractive forces of the particle may trap ions near the surface, further complicating the local electric field and the plasma behavior

[73]. Furthermore, the plasma becomes charge-imbalanced as negative charges are depleted compared to positive charges which has the effect of increasing the overall electrostatic potential within the plasma. Hence, the particle charging phenomenon is one of the most important factors in complicating the behavior of a plasma [74].

Figure 2.3.2.2.1. (a) Higher electron speeds in a plasma compared to ion velocity typically leads to negative charging of a particle. (b) Negatively charged dust particles exert electrostatic forces on electrons and ions, increasing their velocity and changing their paths: in this case creating a higher concentration of positive ions in the particle’s wake due to a “slinging” effect as ion paths are redirected.

When multiple dielectric dust particles are introduced into a plasma region, the accumulated charges around them tend to mutually screen each other, repelling electrons and accelerating ions rapidly away. This screening effect causes each individual particle to charge substantially less than it otherwise would if it were isolated [75, 76]. Moreover, long-range interactions between two or more charged particles dramatically alter the behavior of the system as a whole [77]. Large ensembles of particles can therefore be expected to interact with each other and with the plasma in very complex ways. Other factors that play a not-insignificant role in plasma dynamics in the presence of dielectric particles include: effects of the grain size on charging

[78]; charge fluctuations over particle surfaces [79]; quantum capacitance effects [80]; macroscopic ensemble effects [81]; and secondary electron emission from charged particles [82].

It should be noted that dusty plasmas can be operated in any of the modes discussed in Section

2.3.2.1, including DC discharges.

As the density of particles in a dusty plasma further increases, the manner in which the particles interact with the plasma becomes more complex. At the opposite extreme from a single microscopic dielectric particle is the DBD phenomenon (which can be referred to alternatively as

a “silent discharge” for historical reasons) which consists of an extremely tightly packed “particle bed;” in fact a dense dielectric barrier between the electrodes. DBD is also well-understood and is applied routinely in waste treatment facilities worldwide among other applications. The DBD process is typically conducted at atmospheric pressures and consists of a wide variety of configurations including a solid dielectric barrier placed in between two electrodes as shown in

Figure 2.3.2.2.2. This type of plasma reactor closely resembles an extreme version of the Sekine group reactor: instead of a loose bed of particles between two electrodes at atmospheric pressure, it is a dense plate between two electrodes at atmospheric pressure. However, the presence of a dielectric plate in between the electrodes significantly alters the behavior of the plasma. Since insulating dielectrics cannot pass a current without catastrophic destruction of the system, DBD systems must be operated in AC mode.

Figure 2.3.2.2.2. Simplified schema of the (a) dielectric barrier discharge and (b) atmospheric pressure glow discharge systems. These closely related phenomena illustrate how adding dielectric material changes the behavior of a plasma. Atmospheric pressure gases are often passed through the plates.

With an open configuration like the tube discussed in Section 2.3.2.1, the glow regime is unstable under high pressures and arcs form rapidly. When a dielectric is introduced, however, the arc is interrupted and the plasma assumes a more glow-like character. Instead of a single powerful arc from one electrode to the other, a series of microdischarges on the order of nanoseconds occur across the surface and from the surface of the dielectric to the opposite electrode which are

characterized as either a Townsend or glow discharge depending on the current density [83]. The type and number of discharges, as well as the voltage they occur at, depends on the gas mixture used, its pressure, and the width of the gap. Because the discharges are short-lived and charges tend to be localized near the surface of the dielectric, the gas is not substantially heated, unlike an arc discharge which can easily reach on the order of 103 K. The DBD is considered a more electrically efficient process than an arc as less energy is wasted in heating the gas and is instead put into molecular excitations that promote chemical reactions. For a more detailed analysis of the history and operation of DBD systems, the 2003 review by Kogelschatz is recommended [84].

Applying a second dielectric barrier across the other electrode (Figure 2.3.2.2.1.b) further reduces the arc-like character of the plasma and produces a more diffuse, glow-like character. This phenomenon is known as atmospheric pressure glow discharge (APGD). In some sense, APGD is just DBD with a greater amount of dielectric material used.

Now that we have examined the well-studied extrema of dielectrics in a plasma, we turn our attention to the Sekine group work, which appears somewhere along the continuum from dusty plasma to APGD/DBD. In fact, these plasmas have been studied, and are available in the chemical literature, but their processes are less well-understood. However, by understanding the material in this section the general working principles behind the packed bed plasma reactor will become more evident.

Section 2.3.2.3. The Packed Bed Plasma Reactor As we have seen, the presence of dielectrics greatly influences the dynamics of plasmas (i) near the dielectric surface and (ii) throughout the discharge volume. In extreme cases, such as with

DBD, the system is no longer capable of operating in DC mode due to the presence of the insulating barrier. This is important to note, as the Sekine group claims that no plasma is generated in their

DC PBPR system although current flows through the reactor as shown in Figure 2.3.2.3.1.

Figure 2.3.2.3.1. Experimental electrical parameters ((a) reported voltage and current values used to compute (b) bed resistance) and reported phenomenon used in the Sekine group publications. From 1999 to 2008, some variation of a discharge (pulsed, corona, or spark) are claimed to explain the observations while from 2009 to present an electric field alone is claimed.

As discussed in Section 2.3.2.1, even the presence of a current as low as 10-9 A (1 nA) through a non-conducting medium is considered breakdown (in this case a Townsend or dark discharge). Currents reported by the Sekine group typically range in the 10-3 A (1 mA), placing the discharge type squarely within the normal glow discharge or transition regime for a typical

Crookes tube type experiment. However, as discussed in Section 2.3.2.2, the presence of dielectrics in the plasma drastically alters the plasma behavior. Although current still flows through the system (thereby making it a plasma by definition), the type or behavior of the plasma will have changed significantly in the presence of the particle bed. Inspecting Figure 2.3.2.3.1 reveals that,

although the applied current in the Sekine PBPR experiments remains nearly constant throughout the years, the resultant measured potential has dropped significantly. In other words, the bed resistance has fallen dramatically. One immediately obvious explanation for this is that the volume the gas occupies between the probes has decreased by the addition of the dielectric bed.

In earlier publications from the Sekine group where no catalyst bed was implemented, the plasma occupied the entire space between the probes (e.g. 10 mm). A very high electrical potential is needed to bridge this gap unless the gas completely ionizes and forms an “electrical bridge” or arc, as shown in Figure 2.3.2.1.1.c, where the electric potential needed to sustain discharge drops significantly upon spark formation. When the particle bed is introduced, however, this gap shrinks drastically to 1-3 mm. In many cases, the probes actually contact either side of the bed. The distance that electrons must travel to move from the high-potential electrode has been dramatically lowered. Additionally, as the particles are charged in the plasma, the space between them increases in electric potential as discussed in Section 2.3.2.2, further facilitating transportation of electrons and ions from one electrode to the other thereby lowering the voltage required from the probes themselves. This reduction in operating voltage by applying packed beds of dielectric pellets is a known phenomenon [85, 86] and is, in fact, used extensively for waste and pollution control [87-

89]. This category of reactors (i.e. packed-bed reactors with a plasma) are typically considered to have high electron energy and low plasma density due to the extremely high electric fields generated between the closely-packed particles. The type used in the Sekine group work is known in industry as a single-stage plasma catalysis (SPC) reactor. Two-stage plasma catalysis systems

(TPCs) are also used, but separate the plasma zone either upstream or downstream from the catalytic zone.

Finally, let us examine an interesting figure provided in the 2012 publication by Oshima et al. which is reproduced as Figure 2.3.2.3.2 [47]. When this manuscript was written, the Sekine group was still transitioning from exclusively reporting discharge phenomena into invoking the effects of an electric field alone to explain their results. Inspection of Table 2.3.2.1 indicates that this shift occurred just about the time the group started to study packed catalyst beds in the PBPR design, though it took one or two papers before the story started to change. In the 2012 publication, the Sekine group compared and contrasted the behavior of the PBPR reactor with and without a catalyst bed, the results of which were published photographically. In both cases, the reactor is seen to glow, though less brightly after the particle bed is introduced. No arc is observed in the packed bed case. Considering all that has been discussed in the previous sections, this result makes perfect sense. First, the presence of a dielectric reduces the opportunity for arc discharge significantly. Instead, one expects a series of microdischarges to occur chiefly over the surface of the dielectric and (possibly) in a small channel with the nearest electrode [90]. Second, as the arc is not produced, the gas temperature is not raised to the absurd levels that it would otherwise be.

Hence, the glow is redder rather than bluish-white (indicative of a cooler temperature). In all cases studied, the current flowing between the probes was maintained at a constant value in the 10-3 A range. Oshima et al. describe this current as a “dark current,” which, regardless of accuracy, is still a current and therefore still requires breakdown of the surrounding gas or particle bed to reach the opposite probe. The observations made in the 2012 study, and in all of the Sekine group papers, nicely fit in with the behavior of a SPC reactor and should not be attributed to an EFAC phenomenon.

Figure 2.3.2.3.2. The reactor used by Oshima et al. in 2012 for oxidative coupling of methane over a Sr-La2O3 catalyst. Reproduced from [47].

Section 2.3.3. Practical Considerations of PBPR

In a review published in 2013, Oshima, Shinagawa, and Sekine discuss the utility of plasmas and electric fields [91]. Herein, plasma reactors are defined as: “Systems in which supplied electrons can activate reactants directly in the gas phase to promote the reaction rate.” No definition is provided for what the authors deem “electroreforming.” The only apparent difference between the two methods seems to be the reactor configuration provided, specifically the location of the electrodes. This is despite the fact that, in previous publications, plasma reforming was conducted by the Sekine group in reactor configurations that are now being claimed as electroreformers. Indeed, the type of plasma being examined in the 2013 review is different from those produced by previous studies (dielectric barrier discharge vs coronal discharge), but this is to be expected with configurational changes. The authors provide no support for their claims that the PBPR style reactor operates under an electric field without plasma generation.

A more recent review by Ogo and Sekine attempted to explain the difference between plasma reforming and electroreforming by the number of electrons used per molecule reacted [92].

In essence, Ogo and Sekine argue that electroreforming is sufficiently distinct from a plasma because it operates slightly more efficiently than a plasma. This seems a rather weak argument not based in physical principles and does not account for the fact that electrons must still travel from one electrode to the other in the PBPR reactor. Ogo and Sekine still have to explain by what mechanism electrons travel from the upper probe to the lower in their reactor setup. In point of fact, higher electron efficiency is expected and known to result from a packed bed plasma reactor.

As discussed in Section 2.3.2.2, dielectric particles gain electrical charge in the plasma which causes acceleration of free electrons and increases electron temperature. “Hotter” electrons impart more energy to molecules, facilitating chemical reactions with lower electron consumption [87,

93].

Some readers may be considering the extremely high electric fields inherent in plasma reforming systems and thinking “what makes these fields any different from those in an EFAC study?” Such a question is valid, and indeed, the electric field effects on molecular fragments and ions within a plasma follow the same physics outlined in Chapter 1. The difference lies in the nature of the plasma itself. When discussing EFAC alone it is important, scientifically, to isolate the phenomenon from other excitation pathways as much as possible. In a highly energetic system such as a plasma, the molecular fragments react completely differently than whole, neutral molecules. In fact, there are several feedback mechanisms between the catalyst particles and the plasma that make plasma-enhanced catalysis fundamentally different from EFAC and other forms of traditional catalysis. For example, the active site dispersion on the catalyst is changed by interaction with a plasma [94], new types of active sites are produced [95], and surface area and

macroscopic structural changes are induced [94]. Plasmas and electric fields are intrinsically linked. Hence, if one wants to study the field effect on its own, one must either cleverly design their plasma experiments to vary only the field strength (which is very difficult) or avoid the generation of plasmas altogether as in the case of FI/EM and STM experiments.

Consider also the inherent complexity of an electric field in a PBPR system, assuming that such a system can be constructed which imparts a “pure” electric field to the reactive gas without the generation of a plasma. In such a system, the field lines established through the bed will be extremely complex as shown in Figure 2.3.3.1 over a single particle. As was discussed in Chapter

1, the orientation of a molecule with respect to a field line is immensely important. If a reaction is conducted through an electrified PBPR system, molecules have the opportunity to adsorb on locations of all field directions, regardless of how the field is applied externally. Hence, part of the gas will experience positive fields, part of the gas will experience negative fields, and part of the gas will experience no field at all! From a scientific perspective, this is a difficult system to analyze fundamentally.

Figure 2.3.3.1. Complex field interactions with a particle embedded in an externally applied electric field cause adsorbates to experience different field directions depending on adsorption location.

From an engineering perspective, however, such conditions may be beneficial. Consider a reaction in which a positive field enhances adsorption but retards reaction while a negative field facilitates reaction but limits adsorption. Neither case is obviously better, and detailed experiments or calculations need to be carried out to determine if one has an edge over the other. In a mixed- field reactor such as the PBPR, however, it’s possible that the two effects can work synergistically.

In the hypothetical example given an external field might be set up in such a way that the top half of each particle experiences a positive field while the bottom half experiences negative fields.

Perhaps the molecules could then readily adsorb to the top half and migrate to the bottom half to react. Another possibility is that an alternating field can be used to rapidly switch field conditions and impart the benefits of both fields to the entire particle bed at once. This approach has been tried at least once using the capacitor reactor discussed in Section 2.4.

Section 2.4. The Capacitor Reactor

When a PBPR is operated with no current flowing between the probes, it may be considered a type of capacitor reactor. Of course, this is something of an oversimplification as capacitors require a larger surface area than the narrow probes typically used in PBPRs can provide.

Nevertheless, this is precisely what a capacitor reactor is: two conductive surfaces, separated by a gap, across which an electric field develops with no current flow between them. In this section we will discuss the basic operating principles of a capacitor reactor (Section 2.4.1), past attempts at studying such systems in the literature (Section 2.4.2), and what to consider when designing a capacitor reactor for use in the laboratory (Section 2.4.3).

Section 2.4.1. Operating Principles of a Capacitor Reactor

A capacitor is a device, often used in electronics, which is capable of storing electrical charge. This is typically accomplished by connecting two metal plates to a power source. Electrical charge then accumulates on the plates as current flows through the circuit. Eventually, current decreases as charge builds up on the plates until all current ceases. The total amount of charge that can be stored within a capacitor (its capacitance, C) determines how quickly this charging process proceeds. The potential drop across a capacitor (V) is a function of the applied voltage (V0), the circuit resistance (R), and the total charging time (t):

푡 − 푉(푡) = 푉0 (1 − 푒 푅퐶) 2.4.1

As charge (and voltage) accumulate within the capacitor, an electric field is established between the plates. The strength of the field depends on the geometry of the capacitor and the total charge (or voltage). Gauss’ Law and the following simple physical definitions can be used to evaluate the field strength in a variety of capacitor configurations:

q Φ = = ∮ F⃑ ∙ dA⃑⃑ 2.4.2 ε0

dV F⃑ ≡ 2.4.3 ds

q C ≡ 2.4.4 V where Φ is the electric flux through the Gaussian surface drawn over the capacitor plate, q is the electric charge contained within the Gaussian surface, ε0 is the permittivity of free space, A is the area of integration, V is the electric potential (voltage) across the plates, and s is the linear distance

variable between the plates corresponding to the type of coordinates used (i.e. x, y, or z for

Cartesian and r for cylindrical).

For a parallel-plate capacitor the field strength is:

V(t) F(t) = 2.4.5 kd where d is the distance between the plates. Of course, this assumes an infinitely large pair of plates and does not consider edge effects, where the fields will not be uniform (as they are in the center of a capacitor) and the calculations more complex. Also of interest to the topic of this dissertation are coaxial cylindrical capacitors where the field is uniform in direction but varies in strength depending on radial distance from the center of the capacitor (r):

V(t) F(t, r) = 2.4.6 krln(b⁄a) where b and a are the radii of the internal and external cylinders, respectively. Both geometries are shown schematically in Figure 2.4.1. Note that both Equations 2.4.5 and 2.4.6 are reduced by the dielectric constant of the material between the plates, k:

F⃑ F⃑ = 0 2.4.7 k

Figure 2.4.1. Schematic representations of (a) parallel plate and (b) coaxial cylindrical capacitor configurations.

Field strength in both capacitor configurations is independent of some important spacial parameters: length and width in the case of a parallel plate capacitor and length in the case of the coaxial cylinder capacitor. Both of these capacitor configurations have been investigated for their use in electric field assisted chemistry in the past [36, 99], and the coaxial cylinder design is used in Chapter 6 of this dissertation. As will be discussed in Section 2.4.2, however, this design risks plasma formation through dielectric barrier discharge (DBD) and can result in similar plasma chemistry as PBPR designs.

Section 2.4.2. Relevant Literature

Although there is plenty of literature using coaxial cylindrical electrode configurations to generate a dielectric barrier discharge phenomenon for chemical reaction applications, there do not seem to be any which investigate applied fields without discharge. In fact, a coaxial cylindrical electrode configuration is a fairly common plasma reactor design. Like the PBPR discussed in

Section 2.3, we will briefly consider these uses of the configuration in order to better understand the behavior of such systems, which will be important for the research presented in Chapter 6, as this design is used with modifications to avoid the formation of plasmas.

As mentioned in Section 2.3.2.2, DBDs cannot be produced using direct current. Instead, if a sufficiently high voltage is applied, the dielectric barrier will simply break down catastrophically. Hence, coaxial cylinder plasma reactors are typically operated using alternating current. A variety of electrical and physical parameters are involved in generating and characterizing these plasmas including maximum voltage, current, and frequency. Wang et al. studied the effects of changing voltage, AC frequency, electrode metal type, and CO2 concentration on CO2 decomposition in a glow discharge produced in the annular space between

two coaxial cylindrical electrodes [96]. It was found that increasing the input voltage or frequency of the AC wave generally increased CO2 conversion. Whether this increase is due to changes in the electric field or due to changes in the plasma itself was not investigated. Furthermore, Wang et al. found that increasing the CO2 concentration also increased the overall conversion and efficiency of the plasma reactor. This may be attributed to a simple Le Châtlier relationship or to changes in the dielectric properties of the reactive atmosphere affecting both the field strength and the plasma properties. Finally, it was found that coating the electrodes in different metals also increased conversion. This was not attributed to catalytic behavior, however, as increases in conversion seemed to correlate with increases in the conductivity of the metal used.

The space between the electrodes can also be filled with catalyst or inert particles, which further enhances reactivity. For example, Yu et al. used a packed coaxial cylindrical electrode design to conduct CO2 decomposition in a dielectric plasma [97]. These tests showed that CO2 conversion increased by as much as 800% in the presence of CaTiO3 packing material compared to an empty reactor. A similar study was conducted by Chung et al. which concluded that the presence of a ferroelectric packing material increased conversion during dry reforming of methane due to a higher rate of microdischarges over the dielectric surface [98].

The Sekine group has also studied the use of coaxial cylinder reactors for plasma generation [99, 100]. Much like their work with PBPR, these reactors implement a catalyst bed into the space between the electrodes. It might be expected that the packing material will have a positive effect on conversion for the same reason as a noncatalytic material would (microdischarge density increase). However, the added effects of a catalyst seem to improve the effectiveness of the reactor even further. It should be noted that although most catalyst-bed coaxial cylinder plasma

reformers seem to be configured as a single-stage reactor (i.e. the catalyst bed and plasma generators occupy the same zone), they can also be constructed as two-stage reactors where the catalyst bed is downstream from the plasma generator [101]. Packed bed cylindrical capacitor style reactors with plasma discharges are fairly well-studied systems, and are generally outside of the scope of this dissertation. For further reading on such devices, the 2006 review by Istadi and Amin is an excellent starting point [102].

Studies on the behavior of chemical reactions taking place between capacitor plates without the generation of plasma are difficult to come by. One study by Zhang et al. used a parallel plate capacitor with applied potentials up to 30 V to enhance the reaction of methyl orange with a photocatalyst and UV light [103]. It was found that operating under direct current mode had a small effect on the catalytic degradation of methyl orange, increasing conversion from ~66.5% at

0 V to ~72.0% at 30 V. Alternating current up to 25 V, 3000 kHz did not seem to have an effect.

These tests point to some kind of influence of a weak electric field, the specifics of which were not investigated. The most likely explanations involve the forced movement of acidic protons and other ionic species, given the low field strengths applied.

In another test by Gorin, et al. the rearrangement of cis-stilbene oxide to diphenylacetaldehyde (1) and diphenylethanone (2) over a thin alumina catalyst layer was investigated using a parallel-plate capacitor configuration [104]. In this test, the reactant was dissolved in either acetonitrile or dichloromethane solvents containing a small amount of tetrabutylammonium hexafluorophosphate electrolyte. In these tests it was discovered that the application of 5 V across the plates (separated by 0.5 mm) was sufficient to enhance the (1):(2) selectivity by ~22 times (10.2:1 compared to 1:2.2 with no applied field). It should be noted that

this capacitor reactor was operated in batch mode and the reaction was allowed to reach thermodynamic equilibrium in all tests over 16 hours. This enormous enhancement in selectivity was attributed to the formation of electrolytic double-layers at the electrode-solution interfaces.

Such double-layers form rapidly at low voltages (this paper found no enhancement at 3 V and below) but can create enormous electric fields near the electrode surface due to high concentrations of ions at the interface as discussed in Section 1.5. Since this interface forms at the surface of the catalytic layer where the reactions occur, it is not surprising that the catalytic process should be altered. A similar “double-layer-induced EFAC” phenomenon was observed with so-called

“anion-π” catalysts in an electrochemical cell by Akamatsu et al. [105]. Although these experiments found similar enhancement due to low applied potentials (≤1 V) that is almost certainly due to the formation of electrolytic double-layers, the physics of the apparatus are uncertain as no drawings or descriptions are available. Still, the idea that high-strength artificial fields can be generated by inducing electrolytic double-layer formation in a capacitor-like reactor is an intriguing one, and one which should be investigated further in the future.

Gas-phase reactions within a parallel-plate capacitor were tested using an alternating field by Lee in 1966 [106]. Lee’s reactor consisted of Ni/NiO plates separated by ceramic spacers. These tests showed that increasing the frequency of the alternating current applied initially increased the

CO conversion. At higher frequencies, however, the conversion first decreased then plateaued

(although still remaining higher than the baseline no-field conversion). It is unclear whether plasma was formed or avoided in these tests; Lee claims to have applied a maximum field of

2.2x104 V/cm (2.2x10-3 V/nm). One possibility is that dielectric barrier discharge did occur over the plates at low frequency, but that this discharge was suppressed at higher frequencies. This could explain why the conversion dropped, reaching a steady (but higher than baseline) value at

higher frequencies. If plasma was formed at low frequencies, it could become first more intense until at very high frequencies when the plasma became unable to propagate itself due to the rapidly changing nature of the applied field. From this point onward, only the effect of an electric field on its own is observed. In a 1963 report on high frequency pulsed power systems, Early and Martin

[107] wrote that plasma generation could be arrested by introducing very short pulses of electrical energy:

“By using pulse repetition rates of several thousand per second, several kilowatts of electrical power can be delivered to a […] gas stream by a single set of electrodes. […] Compared to arc-heating methods, the pulsed-corona discharge is diffuse and uniform and the gas flow remains much more homogeneous.”

Plasma discharge suppression using high frequency pulsed power today is a common technique in electrical engineering applications for plasma suppression. As one example, a method from Sandia National Lab for nondestructive electrical probes to locate insulation defects in electrical wire uses high voltage pulse power systems [108-111]. The technique is also used to prevent the discharge that occurs in electrical devices at triple phase boundaries. The application of such high frequency pulsed power systems may be the solution to the question of how extremely high fields can be applied without dielectric breakdown. This is especially important for capacitor- style systems wherein breakdown is expected but must be avoided. The idea of using pulsed power systems is explored further in Chapter 6, where a coaxial cylindrical capacitor design is used in conjunction with a high frequency pulsed power system to generate extremely high electric fields over a catalyst surface.

Section 2.4.3. Practical Considerations of Capacitor Reactors

Capacitor style reactors have a number of benefits that make them exciting candidates for field-enhanced reaction studies. For one, their simple and well-understood physics makes field strength determination and field application easy to understand and apply by anyone. They are also flexible and can be created in a wide range of configurations and sizes, and are easily scalable to a range of different size and throughput requirements. They can also be used with or without a wide selection of solid catalyst particles.

However, the system is not without its drawbacks. Much like the probe-bed-probe style reactors discussed in Section 2.3, the presence of a ground or the close proximity of cathode and anode make dielectric breakdown of the reactive atmosphere extremely likely. This limits the strength of fields that can be applied, and may require the use of complex control systems such as a pulsed power system to prevent plasma formation. Additionally, if a packed bed is incorporated into a capacitor style reactor, it will suffer from the same field irregularity issues as the probe-bed- probe style reactors (see Figure 2.3.3.1). Hence, the system appears less useful from a scientific perspective and more interesting from an engineering perspective.

One potentially useful technique for ensuring homogeneous fields in a capacitor system is to make one of the electrodes out of catalytic material. Although this will dramatically impact the available reactive area, it will be easier to study the individual effects of a positive field versus a negative field. Another possibility is to use rapidly alternating fields. While this does not solve the problem of irregular fields, it at least treats all parts of catalyst particles the same way. As discussed in Section 2.3.3, alternating fields may also allow for the benefits of both field directions to occur at the same time.

Overall, capacitor style reactors can be interesting from both a scientific and engineering perspective, depending on how they are applied. For both the scientist and the engineer, the capacitor’s readily understandable physics makes it an easy system to design, apply, and understand. Furthermore, the engineer will appreciate the capacitor reactor’s scalability and flexibility with regards to configuration and packing material. The scientist, on the other hand, will appreciate a cleverly constructed capacitor reactor for its ability to test purely positive or purely negative fields (given one of the plates is constructed of catalyst material and is the reactive surface). The major drawback of the capacitor style is, of course, the difficulty of achieving extremely high fields while avoiding breakdown of the materials between the capacitor plates—a problem which can be solved by using low applied potentials, applying strong dielectrics, moving one plate very far from the other, or by applying the field as short-duration high-frequency pulses.

Section 2.5. The Integrated Circuit Reactor

Removing one plate entirely from a capacitor style reactor design is, in essence, how an integrated circuit reactor (ICR) design is able to avoid breakdown issues while theoretically achieving extremely high surface electric fields. In principle, the ICR design is simple: integrate a catalyst bed into an electrical circuit and take advantage of surface charges that naturally form during circuit operation. In reality, however, the ICR is difficult to design and to apply. In this section we will take an in-depth look at the ICR from its basic operating physics (Section 2.5.1), a review of ICR designs and studies (Section 2.5.2), and practical considerations of using an ICR

(Section 2.5.3).

Section 2.5.1. Principles of Operation of ICR

ICRs rely on the electric fields generated outside of circuit elements such as wires, resistors, and capacitors during their normal operation. The physics of these fields are often glossed over or not mentioned at all during the course of a normal undergraduate physics education, and so some effort must be invested into understanding them.

Take the simple circuit shown in Figure 2.5.1.1 as an example. Given a source of potential (such as a battery or a power box), electric current will run through the wire. In fact, this is a short circuit and quite a lot of current will flow as the circuit resistance is very low. Nevertheless, we use it as a starting point for discussion. Is there an electric field outside of the wire connecting the terminals of the potential source and, if so, what is the structure and strength of this field near the surface of the wire?

Figure 2.5.1.1. What kind of electric fields are generated around a simple circuit such as this one consisting of only a source of electrical potential and a wire?

The answer to this question has been hotly debated in the physics literature over many decades. Many researchers have denied that such a field exists, and many more have insisted that one must exist. The detailed historical review of this debate by Assis, Rodrigues, and Mania is essential reading for researchers interested in this topic [112]. For our purposes, the debate was fairly well settled in 1962 with a seminal experiment by Jefimenko who used grass seeds scattered atop a thin circuit painted on glass to visualize the electric fields produced around the wires [113].

Jefimenko’s experimental data are replicated as Figure 2.5.1.2.a.

Figure 2.5.1.2. The structure of an electric field outside of a current-carrying wire (a) as first observed by Jefimenko and (b) as later modelled by Assis.

Assis et al. built on Jefimenko’s experimental observation and developed a set of consistent physical models to describe such a system. These models are capable of determining the electric potential (ϕ) at any point within or without the wire, and generate the field lines shown in Figure

2.5.1.2.b:

1 2π l/2 σ a ϕ (r, z) = ∫ ∫ f dφ dz 2.5.1 1 4πε ( 2 2 ( )2)(1⁄2) 2 2 0 φ2=0 z2=−l/2 r + a − 2ra cos φ2 + z2 − z where r and z are the radial and longitudinal direction components of the test point, respectively; a and l are the radius and length of the wire, respectively; ε0 is the permittivity of free space; φ2 and z2 are integration placeholder variables for electric potential and distance, respectively; and

σf is the free charge density over the wire surface which depends on the resistance of the wire (R), current flowing through the wire (I), and the potential applied to the right- (ϕR) and left-hand (ϕL) sides of the wire:

Rε I ε (ϕ + ϕ ) σ (a, φ, z) = − 0 z + 0 R L 2.5.2 f a ln(l⁄a) 2a ln (l⁄a)

Through a series of simplifications and assumptions, Assis et al. were able to represent the electric field (F⃑ ) at any given point outside of the wire (r ≥ a) as:

1 RI RI + 2ϕ r̂ RI ln (l⁄r) F⃑ = − ( z − R) + ẑ 2.5.3 ln(l⁄a) l 2 r l ln (l⁄a) where r̂ and ẑ are the unit vectors in the radial and longitudinal directions, respectively.

These physics are difficult to apply to real situations, as the assumptions involved depend on a length of wire with no bends or kinks. It may serve as a good first approximation to such systems, however, and it is important to at least recognize that such physics have been developed and are available for complex field situations.

Using this information, how should a catalyst be integrated into the circuit given in Figure

2.5.1.1? Note that both the experiment and computational model provided in Figure 2.5.1.2 indicate that the field lines intersect the wire at increasingly perpendicular angles further from the center of the wire. This structure arises due to the presence of a charge gradient from the positive terminal to the negative terminal of the circuit as shown in Figure 2.5.1.3. Hence, connecting the catalyst to the geometric center of the circuit will result in a transition from negative to positive across the surface of the catalyst, yielding mixed effects as discussed with PBPR reactors (Section

2.3.3). Moreover, the field strength is weakest near the center. Optimum placement of the catalyst is therefore as near as possible to one or the other terminal. This not only increases the magnitude of the field applied but also ensures unidirectional fields over the catalyst surface.

Figure 2.5.1.3. Catalyst placement in a simple ICR is essential to proper operation. Placement at the geometric center (orange) will result in weak fields of varying direction. Connecting the catalyst closer to a power source terminal, however, will result in uniform fields that strengthen with increasing proximity to the terminal.

Further manipulation of the field outside of a wire can be accomplished by changing the elements comprising the circuit. Resistors, capacitors, inductors, diodes, and so forth will alter the circuit physics including the external fields generated. For the purposes of this discussion, we focus on the introduction of a capacitor into the circuit. When a capacitor is introduced to a circuit, surface charges develop on the connecting wires similar to that of the simple circuit shown in

Figure 2.5.1.3 except that the circuit now consists of two distinct “legs,” each of which is charged separately. This improves the replicability of reactor construction as field strength and direction do not depend upon precision placement. Figure 2.5.1.4 depicts a schematic of a capacitor-based

ICR design. Note that the capacitor itself does not serve as a catalyst surface nor is it directly involved in the reactor construction—unlike the capacitor reactors discussed in Section 2.4, this capacitor is merely an element of the external circuit connected to the reactor. These physics are similarly tricky to evaluate in the real system, though interested readers are directed to work by

Preyer for a start in developing such models [114].

Figure 2.5.1.4. ICR physics with a capacitor integrated into the circuit in series with the catalyst. Note that the intensity of the colors of the wire indicate the relative density of charge distribution, which is concentrated at the capacitor and power source terminals, but relatively constant on the rest of the wire.

Section 2.5.2. Relevant Studies

Since the fields generated in an ICR are inextricably linked to the physical structure of the

ICR—types of materials, circuit elements, and how they are connected—they are difficult to study, and few attempts have been made at such systems. Still, the benefits of ICRs done correctly can provide a lot of insight into the effects of electric fields on chemical reactions. At the time of this writing, the ICR studies highlighted in this section are the only ones known to the authors to exist and all come from the same group which combined density functional theory (DFT) analysis and experimental data.

The first known mention of an ICR in the literature was reported by Che et al. in 2015

[115]. In this work, the effects of both positive and negative electric fields on water adsorption and reaction were investigated over a Ni catalyst integrated into a simple circuit with a resistor. The study hinted at the complexities that can arise when studying molecules in strong electric fields

for catalytic applications. In this case, although water was predicted and observed to adsorb more strongly to a positive surface (since bonding through the electronegative oxygen atom is more favorable), the positive surface simultaneously repels the electropositive hydrogen atoms pushing them further from the surface. This repulsion makes the positive surface less likely to react with water, decreasing water activation. The opposite effect is true of the negative field: water is less likely to adsorb, but more likely to react once it does. Hence, no single field direction is favored for this simple case.

Che et al. considered more complex scenarios in their later work, where the effects of a field on the full methane steam reforming reaction were considered [116, 117]. In this work, a rigorous analysis of each step in the methane steam reforming reaction was analyzed by DFT and compiled into a microkinetic model, reproduced as Figure 2.5.2.1. Each individual elementary reaction was found to be affected to a different degree by applied fields. Where one step might benefit from a negative field, another might benefit from a positive, and another might get worse in both. Surprisingly, fairly good agreement was observed between the computational model and the experimental investigation with positive electric fields. This was not the case, however, for the negative field experiments where it is hypothesized that unexpected side reactions occurred that were not accounted for in the model.

Figure 2.5.2.1. (a) The microkinetic model used by Che et al. to describe the elementary steps of methane steam reforming. (b) Each of these steps was then analyzed under both positive (red) and negative (black) fields. Arrows indicate that that pathway is favorable under those field conditions. Taken from Ref. [117].

Section 2.5.3. Practical Considerations of ICR

Although the ICR has significant scientific and engineering advantages, it also comes with a number of drawbacks that limit its usability. The scientist will appreciate the ability of the ICR to generate unidirectional fields over the catalyst (e.g. all positive fields) while the engineer will appreciate that it can be operated under more “realistic” pressure and flow rate conditions

(compared to the FE/IM, e.g.). The chief difficulties in ICR application stem from its construction- dependent field strength. It can be very difficult to produce two ICRs that generate the same field conditions because element attachments, geometry, and even the catalyst surface all influence the fields generated and all are difficult to precisely reproduce. Reproducibility is a concern of both the scientist and the engineer, so this limitation may be unsurmountable for both. Some of the reproducibility concerns can be reduced by careful consideration of the circuit elements used. For example, the charge distribution on a wire between a potential source and a capacitor terminal is nearly constant. Integrating the catalyst into this wire can greatly diminish, though not eliminate, the variability that arises with ICR construction.

One additional complicating factor for the ICR is the difficulty of estimating the field strengths generated at the surface. Field direction is generally simple to determine based on the

circuit construction, but field strength depends greatly on the voltage applied, the types of circuit elements, distances between elements, and the structure of the catalyst itself. Complex numerical models can be developed (e.g. based on the methods of Assis et al.) or software (e.g. COMSOL

Multiphysics) can be used to approximate these fields. Chapters 3 and 4 of this dissertation are focused primarily on the challenge of understanding and visualizing the surface electric fields generated within an ICR reactor. This work uses formic acid as a probe molecule to determine the average strength of the field at the catalyst surface. Hence, Chapter 3 begins with an investigation into the nature of catalyzed formic acid decomposition and Chapter 4 leverages this reaction to approximate the strength of fields in a capacitor-arm ICR.

CHAPTER 3: INVESTIGATING FORMIC ACID DECOMPOSITION

This chapter takes a brief hiatus from the topic of field-induced catalysis to examine a more general catalytic problem. It is hoped that the reader now fully grasps the complexities involved in electric field assisted catalysis (EFAC) and understands the difficulties in designing EFAC reactors. As implied in Chapter 1, the details of how EFAC works are dictated by the specific molecules and transition states involved. Before continuing with our EFAC investigations, then, we must pause to consider which chemistry might be most advantageous to study.

As mentioned in Chapter 2, the integrated circuit reactor (ICR) has been tested thus far only with methane steam reforming—a seemingly straightforward reaction that actually contains many complex elementary steps which make analysis difficult. The ultimate goal for a fuel systems scientist or engineer is, of course, to tackle these complex fuel reforming systems (and systems of even greater complexity such as gasoline or jet fuel). In pursuit of these goals, however, fundamental foundational work required for adequate understanding (and more intelligent designing) of the systems is often overlooked. Simpler chemistry ought to be investigated thoroughly before significant advancements can be made on more industrially or commercially relevant systems. To that end the relatively straightforward reaction of gas-phase formic acid decomposition has been selected for analysis. Serendipitously, formic acid has garnered significant interest in the alternative and renewable energy community as an intermittent energy storage medium and/or a candidate for a liquid precursor for in situ hydrogen generation. This concept is explained further in Appendix B.

This chapter begins with a discussion of challenges involved in understanding the mechanism of decomposition for even this simple molecule in the literature (Section 3.1) followed

by my own attempts at elucidating the mechanism experimentally (Section 3.2). A detailed mechanism based on these analyses is then proposed (Section 3.3), and a simple simulation constructed based on this mechanism (Section 3.4) which is compared to the experimental results

(Section 3.5). The chapter concludes with a few notes on applying the principles of EFAC outlined in Chapter 1 to the formic acid decomposition reaction based on the mechanistic understandings gained (Section 3.6).

Section 3.1. Surveying the HCOOH Decomposition Mechanistic Literature

Thermal decomposition of HCOOH occurs via two primary reaction pathways:

HCOOH → H2 + CO2 3.1.1

HCOOH → H2O + CO 3.1.2

Although these reactions have been studied in innumerable systems for decades, details of the mechanism are still surprisingly fuzzy. The chief challenge in determining this mechanism appears to be that none, or few, of the reaction intermediates are readily apparent from observations of the surface (e.g. using in situ infrared spectroscopy). For example, a quite excellent summary of the HCOOH decomposition on metallic surfaces was written by Bond in 1962 which outlines key points of controversy surrounding the adsorption and reaction mechanisms of HCOOH on Ni and other metals [1]. Not too much more is known about this reaction now than was described by

Bond 80 years ago: the vast majority of the decomposition mechanisms proposed from experimental studies are still quite vague and disjointed—molecule fragments appear or rearrange suddenly with no explanation. Several such examples from literature are provided as Figure 3.1.1.

For this reason, a different approach is taken in our own experiments. Rather than hoping for direct

observation of key intermediates, the mechanism is developed from examining a suite of reactive experiments and simulations as described in subsequent sections.

Figure 3.1.1. Four proposed mechanisms from experimental studies over a variety of catalyst surfaces for catalytic HCOOH decomposition: reproduced from (a) Mars et al. 1963 [2], (b) Singh et al. 2016 [3], (c) Criado et al. 1971 [4], (d) Sadovskaya et al. 2017 [5].

Although the mechanistic resolution appears to not have improved over the years, most

HCOOH decomposition studies appear to agree on several important points: (i) that the deprotonation of HCOOH and adsorption of its fragment into formate (HCO*O* (here, asterisks represent a bond to the surface)) occurs rapidly; (ii) the HCO*O* fragment dominates the surface; and (iii) that CO2 production is generally proportional to the amount of HCO*O* available on the surface.

One important breakthrough in the investigation of HCOOH decomposition mechanisms was made by Bandara et al. using picosecond laser jump infrared analysis [6]. In this work, the

authors identified for the first time the presence of a singly bonded HCOO* fragment and proposed a reaction pathway (Figure 3.1.2) that closely resembles that of pathways developed by density functional theory (DFT) analysis [7].

Figure 3.1.2. The transition of inactive HCO*O* to active HCOO* appears to be an important step in the catalytic decomposition of HCOOH.

Section 3.2. Experimental Analysis of HCOOH Decomposition

The general ideas outlined in Section 3.1 provide substantial insight into the mechanism of formic acid decomposition on metal surfaces. To go further, we conducted a variety of tests, described in Sections 3.2.1 and 3.2.2, that were critical for the development of a complete reaction mechanism including both surface- and gas-phase interactions.

Section 3.2.1. Experimental Methods

For the purposes of this study, a molybdenum carbide material was chosen that consisted of cubic molybdenum (II) carbide (fcc-Mo2C) nanoparticles supported on graphene flakes. With an average particle size of 2.1 ± 1.3 nm, the particles were selected because they were hypothesized to have high activity and, due to the metallic nature of Mo2C and the electrical conductivity of the graphene support, was a promising candidate for future EFAC experiments.

The material was prepared by collaborators at the Korea Institute of Energy Research (KIER), and details of the synthesis can be found in our collaborative publication in Applied Catalysis B.

Several experimental tests were designed with the intent of extracting pieces of information from the results which would give insight into specific suspected mechanistic steps or interactions.

These are summarized in Table 3.2.1.1. Each experiment is described in detail in subsequent sections. Aside from these key mechanistic experiments, standard catalyst characterization data was also collected including activation energy (used in the simulations) and turnover frequencies

(TOF; used in the HCOOH Saturation tests). Details of these characterizations can be found in the full publication in Applied Catalysis B.

Table 3.2.1.1. Experiment names and the questions they seek to answer.

Experiment Name Questions CO2/CO Selectivity Which pathway is more difficult over the catalyst? Long-term Does the catalyst deactivate? What causes it to deactivate? Pulse Are CO and CO2 produced simultaneously? H2-blending Does the presence of H* influence the selectivity? HCOOH Saturation Is gas-phase HCOOH involved in the catalytic process?

Section 3.2.1.1. CO2/CO Selectivity Test A large amount of catalyst, ~5 mg was loaded into a quartz tube reactor with 7 mm inner diameter. Note that the support material (Single-Layer Graphene from ACS Material) is extremely low density, roughly 0.038 g/cm3 so even this small mass corresponds to a fairly deep packed bed.

A deep bed was selected for this test in an effort to allow the reactive stream to reach thermodynamic equilibrium. The reactor was then inserted into a ceramic furnace. The catalyst, after H2 pretreatment (60 sccm of 50% H2/Ar at 500 °C over 1 h), was then reacted with 60 sccm of a HCOOH-saturated stream of Ar at temperatures between 270 and 400 °C in 10 °C increments.

The HCOOH-saturated stream was generated by bubbling Ar through liquid HCOOH maintained at 0 °C in an ice bath. The product stream was scrubbed of HCOOH vapors by bubbling through a trap filled with deionized water. The HCOOH-free productr stream was then sent to a real-time

gas analysis mass spectrometer (RTGA-MS; Agilent 5975C) set to sample the product stream once per second.

Section 3.2.1.2. Long-term Test Slightly less catalyst, ~4 mg, was used for the long-term tests to limit the amount of active area that needed to be deactivated (so the test could give deactivation information within a reasonable timeframe). For similar reasons, a high flow rate of 120 sccm of HCOOH-saturated Ar was passed through the bed, and the bath was maintained at 20 °C using a water circulator (Cole-

Parmer polystat 1C6). The reactor was maintained at 380 °C, determined to be the optimum temperature for CO2/CO selectivity from previous tests, for 160 h (one week). Data were again collected by RTGA-MS.

Section 3.2.1.3. Pulse Test Short-duration pulses of reactant (“pulse”) flowing over ~4 mg of catalyst were alternated with long-duration pulses of pure Ar (“purge”). This was accomplished using a 4-way valve connected to a pneumatic actuator that was computer-controlled. The pulse consisted of 15 s of

HCOOH-saturated Ar (0 °C HCOOH bath) and the purge consisted of 120 s of 100% Ar. The reactor was again maintained at 380 °C and the effluent measured with RTGA-MS. Both the inlet and outlet lines were maintained at 100 °C to limit interactions with the tube wall that could cause chromatographic broadening of the pulses.

Section 3.2.1.4. H2-blending Test

As with other tests, ~4 mg of catalyst was loaded into a quartz tube, pretreated with H2, and reacted with HCOOH vapors at 380 °C. The gas flow rate was maintained high enough to ensure kinetic control (>120 sccm) and the HCOOH reservoir was held at 0 °C. To test for the influence of the concentration of H* on the catalyst surface, between 4.6 and 30 sccm of H2 gas

was added to the feed. The Ar and H2 gases were blended together before entering the bubbler to maintain a constant HCOOH partial pressure entering the reactor.

Section 3.2.1.5. HCOOH Saturation Test The catalyst surface was saturated with HCOOH vapors by varying the quantity of catalyst within the reactor as well as the concentration of HCOOH vapor flowing in. This was accomplished by measuring the CO2/CO selectivity in the same manner as described in Section

3.3.1.1 but using 2 and 4 mg of catalyst instead of 5 mg. The HCOOH bath temperature was also changed from 20-60 °C for the 2 mg test, and from 60-80 °C for the 4 mg test.

Saturation of the surface will occur when the “working speed” of the catalyst is outpaced by the reactant stream flowing in—that is, when the turnover frequency of the catalyst is matched or exceeded by the number of molecules flowing into the reactor per active site. Hence, the following dimensionless quantity can be defined for each test condition and used to compare simulation and experiment directly:

mol feed velocity ṅ ( )/S(mol) ṅ = s = 3.2.1.5.1 reaction velocity TOF(s−1) S ∗ TOF where ṅ is the reactant feed rate, S is the number of active sites in the reactor, and TOF is the catalyst turnover frequency.

Section 3.2.2. Experimental Results

The results of the experiments described in Section 3.2.1 are shown in Figure 3.2.2.1. The

CO2/CO production ratio (selectivity) increased nearly monotonically as a function of temperature.

The catalyst was stable for 160 h of continuous HCOOH reforming, though the initial activity was higher than the long-term steady-state activity. Pulses of HCOOH produced CO and CO2

simultaneously, though the CO pulse was much sharper than the CO2 pulse which had a significant tail extending for several times the duration of the reactant pulse itself. Mixing H2 into the feed caused the CO2/CO selectivity to decrease in a nearly linear manner, and adding more HCOOH to the gas stream after saturating the catalyst surface caused a sharp decline in CO2/CO selectivity.

Figure 3.2.2.1. Experimental results for (a) CO2/CO selectivity, (b) long-term, (c) pulse, (d) H2 co-feeding, and (e) HCOOH flow rate tests.

Section 3.3. Developing a Holistic HCOOH Mechanism

The experimental data provided in Section 3.2.2 gives valuable insight into the HCOOH decomposition mechanism. These data provide information about the dynamic gas-surface and surface-surface interactions that occur during catalytic HCOOH decomposition which, combined with mechanistic studies conducted in the literature (from both IR and DFT, as described in Section

3.1), allow for a more complete mechanism to be devised for both the dehydration and decarboxylation pathways of HCOOH decomposition. The experimental data are interpreted in

Section 3.3.1 and the complete mechanism is described in Section 3.3.2.

Section 3.3.1. Interpreting the Experimental Data

From the selectivity data provided in Figure 3.2.2.1.a, the relative ease with which CO and

CO2 are formed can be inferred. The monotonic increase of CO2/CO selectivity indicates that the dehydration pathway (HCOOH ⟶ CO + H2O) occurs more readily at lower temperatures over the catalyst than does the decarboxylation pathway (HCOOH ⟶ CO2 + H2). Based on DFT analysis reported in the literature, this is directly contradictory to what is expected of a reaction that occurs solely on a Mo2C surface. According to Luo et al.: “Formate dissociation into CO2 and hydrogen is the rate-determining step and [HCO*O*] represents the resting state. Our results rule out the possible formation of CO and H2O” [8]. This DFT result is itself directly contradicted by temperature programmed desorption (TPD) data collected by Flaherty et al. who found co- production of both CO and CO2 simultaneously from a C-Mo(100) single crystal covered in

HCOOH [9]. The TPD results are difficult to analyze, however, as all signals are reported in arbitrary units with no axis values provided, so the relative amount of CO to CO2 produced at any given temperature is unknown.

One TPD observation made by Flaherty et al. that is fairly unambiguous, however, is the significant production of CO observed above 627 °C, the relative quantity of which is substantially higher than CO produced at lower temperatures. The authors attribute this CO production to recombination of C* and O* fragments lingering on the catalyst surface at elevated temperatures.

These fragments are supposedly generated during the decomposition of HCOOH. Why these should recombine into CO alone and not CO2 is unknown, as the relative proportion of C* to O* on the surface should be roughly 1 to 2. Additionally, the production of O2 could be expected, leaving behind residual C* which could poison the surface. The TPD study did not examine O2 signals, however, so this is unknown.

Our long-term data provides some insight into the possible presence of surface contaminants indirectly through deactivation data. Since the reactor was operated at 380 °C, we expect the >627 °C C* + O* recombination proposed by Flaherty et al. to not occur, implying a gradual buildup of surface contaminant that should result in deactivation. Deactivation is indeed observed, as the initial activity of around 38% conversion decreases to around 33% over the course of several days. However, this decrease does not continue but, rather, plateaus and remains stable for the rest of the test period. Examination of the catalyst before and after reaction rules out changes in active area due to sintering of the particles. This activity loss is therefore attributed instead to a transient poisoning species, a molecule or molecule fragment which is somehow involved in the reaction but has slow enough kinetics to allow it to build up substantially over time. The C* + O* reaction could still account for this, but as this reaction was not observed until much higher temperatures, this seems unlikely to occur until the surface is significantly crowded by fragments.

At this stage, one might expect a rapid recombination, restoring activity. Cycles of high and low periods of catalyst activity could then be anticipated. Instead, the initially high activity decays slowly until it reaches a new long-term steady-state which holds steady for more than 120 h.

Based on these data, we can infer two mechanistic details that satisfy these observations.

First, the poisoning species being active in the reaction suggests the formate fragment (HCO*O*) as a likely candidate for surface crowding. This is the same structure indicated by Luo et al. in their DFT analysis as the stable precursor involved in CO2/H2 production. Second, since surface- catalyzed low-temperature CO/H2O production was determined to be difficult to produce by Luo and substantial CO production was not observed in TPD by Flaherty until >627 °C, the CO and

H2O produced in our flow-through system may not originate from surface reactions. One possibility is that the CO2-producing reaction dominates the surface, while the CO-producing

reaction is a byproduct of gas-phase or gas-surface interactions. Considering that HCO*O* appears to be a relatively inert species (from the long-term deactivation data), the only other major molecular fragment on the surface that could be involved in a hypothetical gas-surface interaction is H*. With this information, we propose the following broad mechanistic steps for our system:

HCO*O* + * ⟶ H* + CO2 + 2* 3.3.1.1

2H* ⟶ H2 + 2* 3.3.1.2

HCOOH + H* ⟶ CO + H2O + H* 3.3.1.3

The structure of Reaction 3.3.1.3 appears similar to an acid-catalyzed dehydration. This alternative route could explain (i) why CO/H2O production occurs at substantially lower temperatures than inferred by surface-DFT analysis and (ii) why the reaction becomes less dominant at elevated temperatures (due to more rapid loss of H* from the surface).

The pulse and H2-addition experiments provide further validation of this proposed mechanism. First, the pulse tests indicate that CO2 production and CO production arise from different sources. The long tail observed during CO2 production, which persists for many times the duration of the HCOOH reactant pulse, indicates that CO2 is generated from slow-reacting species on the surface of the catalyst: likely HCO*O*. This also supports the findings of the long- term test which indicated that a slow-reacting species was likely dominating the catalyst surface.

On the other hand, the sharp drop in CO production after the HCOOH reactant pulse passes through the reactor indicates that the CO-generating reaction relies on gas-phase HCOOH. These tests are further supported by reactive molecular beam tests conducted by Flaherty et al. [9]. In these tests, a C-Mo(110) single crystal flag is subjected to alternating HCOOH and inert molecular beams.

While the HCOOH beam impinges on the flag the CO2 production signal continually rises. At the

same time, CO is initially high and rapidly decreases to a steady-state. After the beam is removed

CO2 production continues, decaying slowly; CO production immediately drops. These observations all indicate that some kind of gas-surface interaction is involved in the production of

CO.

Blending H2 into the HCOOH feed of our flow reactor allowed us to arbitrarily increase the concentration of H* and determine whether or not this species had an impact on the CO production rate. Indeed, it seemed that as more H2 was added to the feed, more CO was produced relative to CO2. Interestingly, the addition of a small amount of H2 did not have any effect on the selectivity, perhaps even increasing it slightly. However, as discussed in Section 3.4, this observation was replicated faithfully in the Monte Carlo simulations and cannot be attributed to experimental error or detection limits. Instead, it is likely that such small amounts of H2 initially don’t effect the selectivity because the rate of dissociative adsorption of H2 to the surface does not outpace the rate of removal from the surface by recombination.

One final attempt was made at invalidating the gas-surface mechanism. If this mechanism is correct, the rate of production of CO should depend not only on the concentration of H* but also upon the concentration of gas-phase HCOOH. On the other hand, the CO2 production rate should not depend on the concentration of HCOOH in the gas phase as it is produced from HCO*O*.

However, since HCO*O* itself is produced from gas-phase HCOOH, this will only hold true if the surface is already saturated with HCO*O*. The rate of production of CO2 will then be relatively constant, while the rate of CO production will increase as more HCOOH is fed to the system. The

HCOOH concentration variance tests show that, indeed, this is the case. As more HCOOH is fed, the CO2/CO selectivity drops significantly. At very high HCOOH flow rates, however, the surface

appears to become saturated with HCO*O* fragments, limiting H* production and/or mobility, and further increases in HCOOH concentration appear to have little effect.

These data seem to support the idea of a dual pathway mechanism: decarboxylation as a surface-catalyzed mechanism and dehydration as an adsorbate-catalyzed mechanism.

Section 3.3.2. Description of the HCOOH Decomposition Mechanism

Based on our own experimental observations and supporting literature discussed in previous sections, a holistic HCOOH decomposition mechanism is proposed. This mechanism assumes a continuous-flow reactor and likely has little-to-no bearing on batch or surface-only (e.g. in TPD) reactions.

First, it is generally well-established that HCOOH will rapidly adsorb onto solid surfaces undergoing deprotonation in the process. This is supported by both infrared measurements [1, 2,

5, 9-12] as well as DFT analysis [7, 8, 13] and is a logical first step for a surface-catalyzed HCOOH process:

HCOOH(g) + 3 * ⟶ HCO*O* + H* 3.3.2.1

As discussed in Section 3.3.1, the mechanism diverges from here into three pathways: decarboxylation, dehydration, and quasi-deactivation.

During decarboxylation, the HCO*O* fragment decomposes to CO2:

HCO*O* + * ⟶ H* + CO2(g) 3.3.2.2

Exactly how this reaction occurs has been the topic of some debate in the literature.

According to DFT analysis, this could happen as a result of HCO*O* rotating about its axis

(producing H-down HCOO*) or by lying “flat” on its side (producing HCO*O* that is parallel to

the surface rather than perpendicular). However, a realistically crowded surface should tend to favor the upright position, and delicate infrared experiments by Bandara et al. using picosecond laser-induced temperature jumps have verified the presence of the perpendicular, rotated species

[6]. Hence, we assume a similar arrangement in our mechanism.

To complete the decarboxylation catalytic cycle, H* produced from both Reactions 3.3.2.1 and 3.3.2.2 hop around the surface and recombine to produce H2:

2 H* ⟶ H2 + 2 * 3.3.2.3

Dehydration occurs when a fresh HCOOH molecule impinges upon a surface and interacts with H* rather than available surface sites. In this case, an acid-catalyzed dehydration occurs which likely produces the formyl intermediate (HC*O) observed in some IR studies. This intermediate is unstable, however, and is known to decompose rapidly [9], regenerating the catalytic active site,

H*:

HCOOH(g) + H* ⟶ HC*O + H2O(g) 3.3.2.4

HC*O ⟶ H* + CO(g) 3.3.2.5

During quasi-deactivation of the catalyst, the formate fragment (HCO*O*) builds up on the surface over time while Reaction 3.3.2.3 continues. This leads to an eventual depletion of active sites for both decarboxylation and dehydration, which retards the activity of the catalyst. However,

HCO*O* can still proceed through Reaction 3.3.2.2, so both active sites can be regenerated at a rate dictated by the reaction temperature (which determines the rate of HCO*O* decomposition).

The overall mechanism is summarized in Figure 3.3.2.1.

Figure 3.3.2.1. Proposed reaction mechanism for HCOOH decomposition over Mo2C nanoparticles supported on graphene. Hydrogen atoms deposited by the initial adsorption of an HCOOH molecule are marked in red to more easily trace its path through the various cycles.

Section 3.4. Simulating HCOOH Decomposition

A simple Monte-Carlo style simulation was developed to test the proposed mechanism using MATLAB. A basic outline of how the model works and approaches used to emulate the various experimental tests are provided in Section 3.4.1. The simulation results are described in brief in Section 3.4.2.

Section 3.4.1. Describing the Monte Carlo Model

Before beginning each simulation, the user must decide on several physical parameters, these are listed in Table 3.4.2.1 along with typical values used in the simulations presented in subsequent sections.

Table 3.4.1. Input parameters required from the user, which must be defined before the model can be run.

Parameter Name Example Values Lattice size L 600 Run time (2x MCS) x 14 Number of HCOOH in per MCS (percent of lattice) FA_Conc 0.1 Number of H2 in per MCS (percent of lattice) H2_Conc 2*FA_Conc Reaction temperature (°C) T 380 Print lattice image after complete simulation (1 = yes, 0 = show 1 no) Probability of H2 decomposition on the lattice H2_prob 0.01 Perform a pulse experiment? (1 = yes, 0 = no) pulse 1 Duration of pulse (MCS) pulselength 500 Duration of purge (MCS) purgelength 5000 Number of H* hops per MCS HHop 1 Probability of H hopping event Hprob 1 Frequency factor of catalyst A exp(16.01) Activation energy Ea 116. Random number generator seed dumdum

In brief, the model generates an LxL square lattice and attempts to place L*FA_Conc formate fragments at randomly chosen positions. Each HCO*O* placement is always accompanied by an adjacent H* placement. The orientation of the HCO*O* fragment (horizontal or vertical on the lattice) is selected randomly, as is the placement of the H* fragment (if horizontal, either to the left or right; if vertical, either above or below). In the event that the model chooses a site already occupied by HCO*O* for adsorption, the attempt is aborted and a counter is incremented to track the number of desorption events (representing unreacted HCOOH exiting the reactor). In the event that the model chooses a site already occupied by H* for adsorption, one of

two things can happen. If the model is running in “Langmuir-Hinshelwood” mode, the adsorption attempt is aborted and a counter is incremented as a desorption event as if the site were occupied by HCO*O*. If the model is running in “Eley-Rideal” mode, the adsorption attempt is aborted and two counters are incremented: one to track CO production and another to track H2O production.

After the new molecule adsorption phase, each H* fragment has an opportunity to move

HHop spaces randomly about the lattice (only entering empty spaces) with a probability of Hprob.

In the event that an H* attempts to move into a site already containing H*, both sites are cleared and a counter is incremented indicating an H2 production event.

Each HCO*O* fragment then decomposes with a probability dependent upon T, A, and

Ea. When a fragment is due to decompose, it attempts to deposit its hydrogen atom on an adjacent site (depending on the fragment’s orientation with respect to the lattice, horizontal vs vertical). In the event that no site is available, the decomposition event is aborted. A counter is incremented indicating a CO2 production event.

This completes one Monte Carlo sweep (MCS) of the lattice. Subsequent simulation cycles repeats for 2x MCS. Further details for the individual simulations including those using some of the optional functions of the model are described in Sections 3.4.1.1-3.4.1.4.

Section 3.4.1.1. Normal Operation Running the simulation for 28-210 MCS is typically sufficient to achieve steady-state (this may change depending on the concentrations and temperatures used). Selectivity can then be computed by comparing the average number of CO2 production events and CO production events.

Long-term operation simulations were conducted by running for 212-214 MCS.

Selection of appropriate FA_Conc, HHop, and Hprob values is facilitated by tuning the model and comparing to experimental parameters. This is done by computing the CO2/CO selectivity across a range of FA_Conc and HHop/Hprob values and comparing directly to the experimental selectivity curve at a given temperature. The tuning curves used to collect the simulation data in the present work is provided as Figure 3.4.1.1.1. These were collected at a simulated temperature of 380 °C and compared to experimental selectivity values at 380 °C, represented by the horizontal dotted line. The intersection of this experimental line with the curve for FA_Conc = 0.10 occurs at almost precisely 1 H* Hop per MCS; hence, HHop = Hprob = 1 were used for these simulations.

Figure 3.4.1.1.1. Tuning curves for the model. The horizontal dashed line represents the experimental selectivity at 380 °C, and its intersection with the FA_Conc = 0.10 line indicates that the selection of HHop = Hprob = 1 should accurately reflect the catalyst behavior.

Section 3.4.1.2. Pulse Simulation Simulating the behavior of a pulsed reactant test, wherein the reactor feed is switched between a reactive stream containing HCOOH and an inert Ar stream can be toggled by setting the pulse parameter to 1. This will cause the model to run as normal for pulselength MCS and then skip the HCO*O*/H* adsorption events for purgelength MCS. The model alternates between these two modes continually until 2x MCS have passed at which point the simulation ends as normal.

During the “purge” phase of the model, only the HCO*O* decomposition and H* hopping portions of the model will operate. As with the experiment, purge lengths should be selected such that sufficient time is allowed between pulse events such that CO2 production has ceased before more reactant is introduced. If the pulses are too close together, the surface will not be sufficiently renewed and the product pulses will begin to accrue until steady-state is attained.

Section 3.4.1.3. H2-blending Simulation

To simulate the co-feeding of H2 and HCOOH, the user must set H2_Conc to a value greater than zero. This works similarly to FA_Conc in that the actual number of molecules introduced per MCS is entered as a fraction of the lattice size. The only change to the model operation is that an additional adsorption step is introduced after the adsorption of HCO*O*/H* fragments wherein two adjacent H* fragments are randomly and simultaneously adsorbed to the surface until H2_Conc adsorptions have been attempted. The low H2 adsorption strength of the catalyst surface is represented by the H2_prob parameter, which represents the probability that an adsorption event will be successful. Hence, if the model selects an occupied site for H2 adsorption or if the attempt does not succeed the adsorption probability check, the attempt is instead aborted and a counter is incremented indicating that H2 has exited the reactor.

Section 3.4.1.4. HCOOH Saturation Simulation Although no special functions are required to simulate the HCOOH saturation experiments described in Section 3.2.1.5, careful consideration is needed to accurately compare the experimental data to the simulation results. Since it can be difficult to convert the simulated flow conditions to real concentrations or flow rates, some other parameter is needed which can be easily determined for both the experiment and the simulation—hence the use of the dimensionless

parameter described in Section 3.2.1.5. The same number can be used to describe the simulated lattice.

The simulated TOF can be determined by running the simulation at low feed concentrations and computing the number of CO and CO2 molecules produced per MCS and normalizing by lattice size (simulation TOF will have units of MCS-1). The simulated feed rate is represented in terms of molecules per MCS:

units 3.4.1.4.2 ṅ ( )/S(units) ṅ L ∗ L ∗ FA_Conc FA_Conc MCS = = = TOF(MCS−1) S ∗ TOF L ∗ L ∗ TOF TOF

Section 3.4.2. Results of the Simulations

Results for the simulated reactions are provided as Figure 3.4.2.1 and compared directly to the experimental values.

Figure 3.4.2.1. Simulated formic acid decomposition following a Langmuir-Hinshelwood-type decomposition for CO2 production and an Eley-Rideal-type decomposition for CO production using kinetic parameters for a Mo2C/graphene catalyst. (a) Simulated CO2/CO selectivity values at a range of temperatures; (b) simulated long-term behavior at 380 °C; (c) product formation after a short-duration pulse of reactants; (d) simulated CO2/CO selectivity change as a function of increasing H2 feed concentrations; and (e) change in CO2/CO selectivity as a function of increasing HCOOH feed rate.

Section 3.5. Comparing Experiment and Simulation

Figures 3.4.2.1a, b, and d compare the simulated and experimental data directly. In these scenarios, agreement is very good between the two situations. Of particular interest is the apparent lack of impact of co-feeding H2 below H2/HCOOH ratios of 6 in Figure 3.4.2.1.d. Explanation of this phenomenon from the mechanism itself is difficult, and may be due to the relative rates of H2 adsorption and desorption—the fact that the simulation independently exhibits this behavior increases confidence in the proposed mechanism.

Although the pulse (Figure 3.4.2.1.c) and the HCOOH saturation (Figure 3.4.2.1.e) tests do not reflect the experimental data in a 1-to-1 manner, their general behavior is similar enough to the experiment to provide some insight into the mechanism. The pulse data indicate a long-term

CO2 production after the initial reactant pulse, whereas CO production ends immediately after stopping the pulse. This is a consequence of the fact that CO is produced only when gas-phase

HCOOH collides with the surface, while CO2 is produced from lingering HCO*O* fragments which take some time to clear from the surface.

Section 3.6. Implications of the Mechanism for EFAC

The elucidation of this dehydration mechanism allows for a slightly more detailed analysis of the formic acid decomposition reaction in an applied field than was possible with our rudimentary knowledge in Section 1.4.

With the knowledge that H* is an important catalytic active site rather than simply a temporary intermediate for H2 production, the effect of a field on dehydration should be revisited.

Consider the reaction of formic acid on Ni (which will be used as the catalyst in subsequent chapters for its conductive properties). In this case the active site and H2-producing intermediate

will be Ni-H. The net dipole moment of this group is negative with respect to the surface with a magnitude of ~0.05 D [14]. Hence, a crude analysis of this species suggests that it should be stabilized in a negative surface field. In fact, the adsorption of H2 onto Ni surfaces was studied by

Che et al. as part of a greater microkinetic model of methane steam reforming. It was found that the specific rate constant for hydrogen desorption from a Ni surface (2 H* ⟶ H2 + 2 *) increased by 27.8% and the equilibrium constant increased by 33.3% in a negative field [15]. In fact, both fields directions enhanced this reaction. This is likely due to polarization of the H2 molecule itself rather than any inherent stabilization of the H* fragment [16, 17]. A summary of expected field directions needed to facilitate each elementary reaction is provided as Figure 3.6.1.

Figure 3.6.1. Field directions needed to facilitate each mechanistic step of formic acid decomposition based on dipole and charge analysis. Red arrows correspond to positive fields, black arrows to negative fields, and blue arrows indicate that neither field is beneficial.

Step 1, adsorption of HCOOH to the surface, is most likely to be facilitated by a positive field since the HCO*O* fragment will be stabilized—the surface is positive while the O atoms bonding the fragment to the surface are negative. Step 2, transition of the stable HCO*O* fragment into an unstable HCOO* fragment, is more rapid in a negative field since it destabilizes the O- surface bonds and the field is antialigned to the HCO*O* surface dipole moment. Since this step

is rate-determining, it may be a safe assumption to say that this will have the biggest impact on the reaction. Step 3 should also be improved by a negative field, as the C-H bond is more likely to break in a negative field. Step 4, as discussed previously, will be more difficult under both field conditions. For the same reason, Step 5 will be more difficult under both field conditions since H* is stabilized and will be less reactive. Steps 6 and 7 are expected to be improved by a negative field since water and CO are both destabilized in a negative field.

Two major conclusions can be drawn from this superficial analysis: (i) the rate-determining step of decarboxylation is improved by the presence of a negative field and (ii) the catalytic site for dehydration is stabilized by the presence of a negative field. Hence, from a fully kinetic point of view the following predictions can be made using this analysis as well as the discussion from

Section 1.4:

1. CO2 production should increase as HCO*O* reaction is facilitated 2. H2 production may a. decrease as H*-H* interactions are made less favorable b. increase as H* concentrations increase across the surface 3. CO production may a. decrease as HCOOH-H* interactions are made less favorable b. increase as H* concentrations increase across the surface

Because the nature of the effect of the field will depend greatly on the exact extent to which each of these effects contributes to the overall reaction, any attempt at using a simple kinetic “rule of thumb” analysis based on simple dipole analysis quickly becomes a complex problem requiring in-depth study. Detailed density functional theory predictions are needed to create a microkinetic model in order to make accurate predictions about the kinetics of formic acid decomposition using

EFAC. This study should also provide information about the gas-surface and gas-adsorbate interactions including the initial adsorption of formic acid (Step 1) and possible H*-catalyzed

dehydration (Steps 5-7). Furthermore, additional transition states or side-reactions may arise due to the influence of the field that may not otherwise be easily predicted. For example, formic acid dimerization has been shown to be enhanced in the presence of strong fields at low temperatures

[18, 19]. This product or transition state may begin to play a role in the high-field chemistry of formic acid at high temperatures, as well. Although such detailed DFT analyses may serve as an interesting (and useful) scientific exercise for researchers to tackle, the depth and rigor needed to analyze an individual reaction at such a fundamental level will pose a significant hurdle for future designers of EFAC systems to overcome. For this reason, a more rapid and straightforward thermodynamic approach is pursued in Chapter 4.

CHAPTER 4: ESTIMATING AND VISUALIZING THE FIELD USING

REACTIVE FORMIC ACID PROBES AND SEM IMAGING

Understanding the kinetics of even simple catalytic reactions in an electric field is no trivial task. Even with higher-resolution knowledge of the mechanism of formic acid decomposition gained in Chapter 3, simple back-of-the-envelope analyses are impossible due to inherently competing effects. For a truly rigorous EFAC design from a kinetic perspective, detailed study using density functional theory and microkinetic analyses are needed. The creation of these models requires dedicated and skilled computational researchers and may take many years to construct and fully understand, particularly when approaching anything more complex than a unimolecular decomposition with two reaction routes. The complex interactions between all of the possible reaction pathways, their associated transition states, and complications due to physical irregularities in the experimental system require intense study and make the model difficult to understand and apply. One microkinetic study of formic acid decomposition on Au catalysts has been produced, however this study does not investigate any gas-adsorbate interactions as described in the mechanism proposed in Chapter 3 [1]. This is likely because (i) the Au catalyst used by the modelers was shown experimentally to have zero activity toward CO production and they simply weren’t looking for these types of interactions and (ii) DFT models alone will not predict such interactions unless they are intentionally set up to search for these. This latter point is because DFT models typically start with clean surfaces or adsorbates on a surface, rather than crowded surfaces with a reactive atmosphere due to limitations in computing power. Still, such a model could be developed and the kinetic effects of a field tested, provided time and resources are available. This is discussed more in Chapter 7.

A different tactic is therefore needed to quickly assess the viability of potential field- reforming systems and to guide researchers and systems engineers and operators towards ideal operating conditions (e.g., choosing the correct field direction). Fortunately, a less computationally intensive approach is possible by analyzing the thermodynamics of a reaction rather than its kinetics. Such an analysis may be beneficial for its simplicity compared to a kinetic analysis.

This chapter introduces a thermodynamics modelling approach using formic acid decomposition over Ni. Section 4.1 outlines the theory underpinning this technique as well as the derivation of key equations. This technique is then implemented and used to (i) predict changes in formic acid decomposition selectivity in the presence of electric fields and (ii) estimate the strength of an applied electric field within an experimental system in Section 4.2. To further support the approach and increase understanding of the complex physics of electric fields at a catalyst surface, a COMSOL simulation of the surface is presented in Section 4.3. The structure of the field is then probed experimentally using scanning electron microscopy in Section 4.4 to verify the COMSOL simulation. Finally, the thermodynamic and imaging approaches are united in Section 4.5 to estimate the maximum field strength generated at the catalyst surface. This chapter is a summary of data submitted to Angewandte Chemie.

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Section 4.1. Predicting Field Strength

As discussed in Chapter 1, the thermodynamics of reactions in an electric field can be described using a van’t Hoff-like relationship [2]:

∂(ln K) ∆μ − ∆αF = 4.1.1 ∂F kBT

where K is the equilibrium constant of the reaction, F is the field strength at the catalyst surface,

∆μ and ∆α are the changes in dipole moment and polarizability of the reaction, kB is the Boltzmann constant, and T is the reaction temperature. ∆μ and ∆α for the formic acid decomposition reaction are computed in Table 4.1.1.

Table 4.1.1. Parameters needed to compute the change in electric moment of the formic acid decomposition reaction based on its two overall reaction pathways. Physical data taken from the CRC Handbook of Chemistry and Physics, 99th Edition.

Reaction Dipole moment change (D) Polarizability change (Å3) (1) HCOOH → H2 + CO2 (0.00 + 0.00) - (1.40) = -1.40 (0.79 + 2.9) – (3.4) = 0.3 (2) HCOOH → H2O + CO (1.80 + 0.14) – (1.40) = 0.54 (1.5 + 0.12) – (3.4) = -1.78

The selectivity of the reaction is taken to be the ratio of the reaction rates (r푖) of the desirable (Reaction 1) and undesirable (Reaction 2) pathways:

r1 S = 4.1.2 r2

Experimentally, these rates can be measured by determining the evolution rate of CO2 and

CO (or H2 and H2O). Thus, the selectivity can be rewritten as:

ṅ CO [CO ]V̇ [CO ] S = 2 = 2 = 2 4.1.3 ṅ CO [CO]V̇ [CO]

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where ṅ i and V̇ represent the molar flow rate of species i and the volumetric flow rate of the stream, respectively, and [i] represents the concentration of species i in the stream. The equilibrium constants can also be expressed in terms of concentrations (assuming standard conditions):

[H ][CO ] [CO ]2 K = 2 2 = 2 1 [HCOOH] [HCOOH] 4.1.4 [H O][CO] [CO]2 K = 2 = 2 [HCOOH] [HCOOH]

Here, [H2] = [CO2] and [H2O] = [CO] since both reactions theoretically produce equimolar quantities of each product. Combining Equations 4.1.3 and 4.1.4 indicates that selectivity is dependent on the square root of the ratio of the equilibrium constants:

K S = √ 1 4.1.5 K2

Combining Equations 4.1.5 with Equation 4.1.1 (after integration) yields a simple relationship for the selectivity of formic acid decomposition in the presence of an electric field:

1 1 2 ((∆μ1−∆μ2)F+ (∆α1−∆α2)F ) 2kBT 2 4.1.6 S(F, T) = S0e

Equation 4.1.6 can be used to make predictions about the thermodynamic changes of formic acid decomposition, which will depend on both the reaction temperature and the applied field. An example of such a prediction is shown as Figure 4.1.1. This analysis does not suffer from the ambiguity of a simple structural analysis when lacking computational information, but it is only applicable to a system in thermodynamic equilibrium. Reactors operating under kinetic control should not be assumed to obey the same trend.

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1000

100 -10 V/nm

10 -1.0 V/nm

1 1.0 V/nm

/CO Selectivity /CO 10 V/nm 2 0.1

CO No-Field Data 0.01 Negative Field Comp. Positive Field Comp. 0.001 200 220 240 260 280 300 320 340 360 380 400 Temperature (°C)

Figure 4.1.1. Predicted selectivities (red and black lines) were calculated using Equation 4.1.6 and experimental formic acid selectivity over Ni catalysts (blue line) for fields ranging in strength from 1.0 to 10 V/nm.

Section 4.2. Measuring Field Strength using Thermodynamics

To accurately test the effects of an applied field on catalytic formic acid decomposition, a suitable reactor design must be chosen that will avoid (i) mixed-field effects and (ii) plasma generation. The integrated circuit reactor (ICR) described in Section 2.5.4 meets these criteria.

Additionally, this design allows for the field to be easily imaged in the SEM as described in Section

4.3—something not readily accomplished with any other design. This section describes the construction of such a reactor and the test parameters used to collect the field-enhanced selectivity measurements needed for implementation of the method developed in Section 4.1, and the results of the subsequent experiments.

Section 4.2.1. Reactor Fabrication and Implementation

The ICR used for these tests has been slightly modified from the one described elsewhere

[3-5]. For this study, a single disk of Ni foam (Goodfellow) serves as the catalyst. Ni microparticles on the order of 95 µm diameter (Alfa Aesar) were sintered to the foam to (i) increase surface area

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and (ii) enhance the field strength (see Section 4.5). This was accomplished by spreading a 2:1 (by mass) suspension of particles in an organic binder (Heraeus) evenly over the top and bottom of the disk and sintering at 800 °C in 50% H2 for 4 h. The catalyst is contained within a quartz tube

(Quartz Scientific, 7 mm ID) and connected to the circuit by Ag wires fed through small holes cut into the sides of the tube. The wires are attached to the catalyst by threading through holes punched in the edge of the catalyst disk; slits in the quartz tube are sealed with ceramic paste (Ceramabond

552, Aremco).

This assembly was inserted into a ceramic furnace (Watlow) controlled by a digital PID temperature controller (Cole-Parmer DigiSense). The thermocouple, electrically insulated from the circuit with a quartz sheath, was inserted into the reactor through Swagelok Ultratorr fittings and brought to just below the catalyst disk. The reactor was then connected to an electrical circuit consisting of a DC power source (VOLTEQ HY20010EX) and a pair of capacitors connected in series (Rubycon, 820 μF, 200 V). This setup is depicted schematically in Figure 4.2.1.1.

Figure 4.2.1.1. Schematic depiction of the ICR used for this study configured for the application of a negative electric field.

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Lines connecting the inlet and outlet of the reactor to the fuel reservoir and mass spectrometer, respectively, were independently heated using heating tape. The inlet line was precisely controlled to 100 °C (to preheat the reactants) using a Cole-Parmer DigiSense PID temperature controller while the outlet line was maintained between 100 and 200 °C (to prevent condensation of products) using a Variac.

Section 4.2.2. Test Conditions

The inlet stream for all tests consisted of Ar bubbled through liquid HCOOH submerged in a temperature-controlled water bath. The bath temperature was controlled using a coil of copper tubing connected to a water circulator (Cole-Parmer).

Selectivity data were collected across a range of temperatures until conditions were found in which thermodynamic equilibrium was reached. Although data were collected at other temperatures, only those at the thermodynamic equilibrium point are analyzed to avoid competing kinetic effects. For this reactor design with one catalyst disk (which was selected for its simple construction for the SEM imaging portion of the study), the operating temperature used was 350

°C. At this point, the kinetics were sufficiently fast enough to achieve equilibrium over the low- area catalyst.

Catalysts were pretreated in flowing H2/Ar (50%) at 500 °C for 30 min prior to each test.

After cooling to reaction temperature, the stream was switched to Ar bubbled through 10 °C liquid

HCOOH. For applied-field tests, the power source was always turned on after pretreatment but before HCOOH flow began.

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Section 4.2.3. Results

The effects of applied fields on CO2/CO selectivity during HCOOH decomposition over a

Ni catalyst at 350 °C are provided in Figure 4.2.3.1. As predicted from the thermodynamic model

developed in Section 4.1, a negative field improves CO2/CO selectivity while a positive field decreases selectivity.

4.00

3.75

3.50

/CO Selectivity /CO 2

CO 3.25

3.00 Negative None Positive Applied Field

Figure 4.2.3.1. The effects of an applied field on formic acid decomposition over a nickel foam catalyst at 350 °C.

These data can be used to estimate the strength of the fields generated over the catalyst surface. Rewriting Equation 4.1.6 as a quadratic expression (Equation 4.2.3.1) allows for direct calculation of the surface electric field strength given a particular selectivity ratio with and without the applied field:

2 S 0 = (∆∆α)F + 2(∆∆μ)F − 4kBTln ( ) 4.2.3.1 S0

−(∆∆μ) ± √(∆∆μ)2 + 4(∆∆α)k Tln(S⁄S ) F = B 0 4.2.3.2 (∆∆α)

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where ∆∆μ = ∆μ1 − ∆μ2 and ∆∆α = ∆α1 − ∆α2. Inputting the data into Equation 4.2.3.2 yields average field strengths over the catalyst surface of -0.25 and 0.16 V/nm for the negative and positive measurements, respectively. Note that, although these fields sound extremely high (i) this is the field strength measured only within a few Ångströms of the surface, where catalysis occurs, and (ii) this is still two orders of magnitude smaller than field strengths generated in field ion microscopes, within enzyme pockets, or the strength predicted to strongly affect molecular orbitals: around 10 V/nm.

Section 4.3. Modeling Surface Field Physics

To independently verify the field strength measurements from first-principles, a COMSOL model of the catalyst was created. A simplified version of the catalyst disk was used which consisted of a square 1 mm thick Ni plate riddled with 500 μm diameter holes within which 95 μm diameter particles were suspended. The plate was modelled as connected to an external circuit with a 200 V bias via Ag wire attached at the center of the plate.

As shown in Figure 4.3.1, the areas of highest field strength on the catalyst are on the catalyst particles and walls of the pores in which the particles rest. Additionally, the presence of the particles has the effect of more evenly distributing the field across the surface of the catalyst, rather than concentrating it in the region just around the wire attachment.

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Figure 4.3.1. (a) The geometry used to model the Ni foam catalyst. (b) Predictions for field distribution over a catalyst disk with no particles and (b) with particles distributed through the pores.

The magnitude of these modelled fields in these hot-spot regions, however, were several orders of magnitude lower than the highest field strength measured experimentally. Using a reactive chemical probe to measure the field strength will necessarily bias the sample towards the measurement of catalytically active sites. These sites tend to be at edges, kinks, holes, and other defects on the surface. Incidentally, surface defects also dramatically increase surface field strength. Hence, the field measurements via reactive probes may overestimate the average electric field greatly. On the other hand, we cannot include the presence of these defects nor compute their effects on the overall field in the COMSOL model, so the COMSOL model likely greatly underestimates the strength of the field. However, the preferential measurement of surface field strengths around active sites may be useful to the researcher seeking to understand chemical reactions in an electric field. Although the estimated field strengths were much lower than expected in the model, the overall structure should still be accurate. We sought to validate this with experimental visualization of the field using scanning electron microscopy.

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Section 4.4. Field Visualization and Mapping

Several methods have been developed for visualizing electric fields with the naked eye.

Jefimenko was the first in 1962 to do so using grass seeds scattered on a glass plate over an electrical circuit [6]. This test is similar in many ways to the classic visualization of magnetic fields using iron filings first conducted by James Clerk Maxwell. The difficulty in measuring electric fields using similar techniques is (i) electrical dipoles are needed to interact with the field, (ii) said dipoles must be visible to the naked eye for the demonstration to be successful, and (iii) very high surface fields are required to have sufficient strength at macroscopically visible scales.

Grass seeds were ingeniously used to overcome this first two problems; they work not because they contain macroscopic electrical dipoles, but because they are electrically neutral insulators. Neutral insulators are polarized in the field, creating transient electrical dipoles which can then align in the field. This is similar to the “ping pong ball on a string” demonstration used in many introductory physics courses to explain the concept of polarizability.

The final issue (that of field strength) was solved by simply subjecting the circuits to 10,000 volts. Even so, Jefimenko reports that the seeds required jostling to encourage pattern formation.

Nowadays, of course, such high voltage systems might be frowned upon for classroom use.

In a similar vein, Jacobs, de Salazar, and Nassar developed another classroom demonstration of electric fields outside circuit elements in 2009 [7]. In this case, a mixture of polymeric tetrafluoroethylene (PTFE) suspended in oil was used as the visualization medium.

Upon application of the field, the PTFE molecules (neutral macromolecular insulators) align and cluster in the field producing visible field lines. This approach “only” 7 kV to the circuit, which may still be frowned upon as a classroom demonstration in many cases.

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Nevertheless, these techniques work well for macroscopic visualization and could make nice demonstrations if approached in a safe manner. For scientific investigations, however, the application is limited. For one, visualization is impossible at the scale of micro or nanometers where catalysis is conducted. Additionally, these data are difficult to extend beyond the qualitative realm.

Electron microscopes utilize information carriers that are both countable and permanently electrically charged providing a promising avenue to allow for small-scale quantitative field visualization and mapping. Although we could find no mention of the use of a scanning electron microscope (SEM) to visualize electric fields over materials directly, there are many instances of methods similar to what we describe used for other technical purposes. For example, the sample is often described as being held at an electrical bias relative to the detector in order to manipulate the image brightness, contrast, and resolution. These manipulations are possible due to changes in the number of electrons emitted from a sample surface experiencing an electrical bias [8].

Section 4.4.1. Experimental Setup

All measurements were conducted using a Quanta 200F from FEI. A custom electrical feedthrough was installed in the sample chamber to allow for sample connection to the external circuit during imaging. Catalyst samples were wired with Ag wires in the same manner as during selectivity measurements and glued to the sample holder using a nonconductive polymer glue to electrically isolate them from the SEM stage. After sealing the chamber, the electrical feed-through was connected to the same circuit used in the selectivity tests.

Brightness and contrast were adjusted only prior to imaging, during site selection and focusing. It is necessary here to anticipate the expected change and adjust the beginning image

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quality accordingly. For example, applying a negative field causes more secondary electrons to be ejected from the surface, increasing sample brightness. Prior to this, the sample should be made very dark, otherwise portions of the image may exceed the maximum brightness and prevent quantification of the image.

Section 4.4.2. Image Processing

An example of image brightening of a catalyst sample as a negative potential is applied across the surface is provided as Figure 4.3.2.1.

Figure 4.4.2.1. A Ni foam disk connected to the negative terminal of a capacitor charged to (a) 0, (b) 100, and (c) 200 V.

Quantification of the change in brightness allows for direct correlation with the experimental selectivity measurement. This quantification can be carried out easily using

MATLAB, since black-and-white images imported into MATLAB are automatically converted into matrices with each pixel assigned a value between 0 (black) and 255 (white).

To begin, the .tif image files can be imported directly to MATLAB by dragging and dropping into the interface under “Current Folder.” Double-clicking will open a new window (the

“Import Wizard”) with information about the image. It is recommended to rename the variable at this point to make it easier to work with (simple, representative names like V0 and V200 for the 0

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V and 200 V images, respectively, work well). Clicking “Finish” imports the image as a matrix variable.

Before any calculations are conducted on the new variables, they should be converted into doubles using the following commands (using the example variable names suggested previously):

V0 = double(V0); 4.4.2.1 V200 = double(V200);

Subtracting and normalizing creates the “difference image” that is the ultimate goal of this analysis. It is important to remember that brighter images are whiter and will contain pixels of higher value (closer to 255) and that these brighter images correspond to negative potentials.

Hence, the difference image can be computed without error by using the command:

dV200 = (V0 – V200)/255; 4.4.2.2 where dV200 will be the new variable containing the difference image. With negative fields, this command subtracts the brighter image from the darker image (e.g. 255 – 0), producing a negative result representative of the negative field generated. With positive fields, on the other hand, this command subtracts the darker image from the lighter image (e.g. 0 – 255), producing a positive result representative of the positive field generated.

To save these difference images for later use, the variable can be exported to an Excel file using the following command:

xlswrite(‘dummy.xlsx’,dV200); 4.4.2.3

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which should generate an excel file named “dummy.xlsx” in the current folder window. This can be dragged directly onto the desktop or into a thumb drive and renamed for saving and further analysis.

Section 4.5. Combining Techniques

The average field strength estimates from Section 4.2 and the field visualizations from

Section 4.4 can be combined to produce “topographical maps” of the surface electric fields as well as to estimate the maximum fields generated in a given area. To start, all pixels2 in the difference images created using the process described in Section 4.4.2 are averaged to obtain an “average change in brightness.” Since the selectivity data necessarily represent an average value over the catalyst surface,3 the two values can be directly correlated. Moreover, since the difference in brightness is a change, these can be compared across different tests and samples. Correlating the average change in brightness and the average surface field yields the calibration curve presented in Figure 4.5.1 which can be used to convert difference in brightness to field strength.

0.2

0.1 F = 1.74DB 0.0 R2 = 0.942

-0.1

-0.2

-0.3

Average Field Strength (V/nm) Strength Field Average -0.15 -0.10 -0.05 0.00 0.05 Average Change in Brightness (a.u.)

Figure 4.5.1. The SEM field strength calibration curve created by combining experimental data collected in Section 4.2 with the SEM brightness imaging conducted in Section 4.4.

2 Except those of the data bar at the bottom of the image 3 Technically, these are an average over the active sites, but these cannot be distinguished visibly in SEM

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By applying the calibration curve to the difference images, contour plots can be created to represent the surface field strength across the catalyst. Furthermore, this application allows for the estimation of the maximum field strength generated at the surface as well as its location. As seen in Figure 4.5.2, these “hot spots” tend to be around the edges of catalyst pores and the surfaces of particles. Note that only small sections of the sample can be converted into contour plots at one time due to computational limitations.

Figure 4.5.2. An analysis of a particle in a pore, taken from the catalyst disk imaged in Figure 4.3.2.1. (a) Standard SEM image close-up of one particle in a pore, (b) the difference image generated by subtracting the standard image from one taken under a negative field and (c) its corresponding topographical map. (d) Difference image generated by subtracting the standard image from one taken under a positive field and (e) its corresponding topographical map.

Although these measurements do not indicate that field strengths of the order necessary for molecular orbital rearrangement are achievable, they are still sufficiently high to induce ion transport and molecular orientation changes as discussed in Chapter 1. Hence, reactions relying on transport or orientation effects primarily (like formic acid decomposition) may be good candidates for review. We turn our attention to the methane steam reforming reaction in Chapter 5 with a particular focus on the behavior of water at the catalyst surface.

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CHAPTER 5: METHANE STEAM REFORMING IN AN ICR

With a more complete understanding of the effects of an electric field on simple reactions, as well as greater knowledge of the field structure over the nickel foam catalysts used for simple integrated circuit reactor designs, we return to more complex and industrially relevant reactions.

The steam reforming of methane (MSR) is an important process used to generate hydrogen gas:

CH4 + y H2O ⟶ (y + 2) H2 + COy 5.2

A more detailed discussion of the relevance of this reaction is provided as Appendix B.

Several detailed computational studies have been conducted on Ni catalysts for MSR in the presence of surface electric fields up to 10 V/nm. From these studies, two findings are particularly interesting. First, that water adsorption to the catalyst surface (hence effective water concentrations) can be improved by the presence of strong positive surface electric fields [1]. As both a consequence of this increased H2O adsorption and as an independent effect of the applied field, coke formation on the catalyst surface is suppressed. Both of these predictions were supported with some experimental data. The research presented in this chapter utilizes the integrated circuit reactor design characterized in Chapter 4 to conduct more detailed experimental investigations of the effects of applying a positive field to Ni catalysts under MSR conditions, along with some computational support, and is a summary of research published in Applied

Catalysis B.

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Section 5.1. Experimental Details

A stack of two Ni disks with Ni microparticles were prepared as described in Section 4.2.1.

These disks were then sintered together at 800 °C to make a single conductive catalyst bed. Ag wires were attached to this bed using Ag paste (SPI Supplies) and the assembly was inserted into a quartz reactor and connected to the external circuit as described in Section 4.2.1. The external circuit for these tests consisted of a power source and a resistance decade box set to 11 MΩ.

The catalysts were pretreated with 50% H2/Ar at 800 °C prior to reaction at 750 °C. The reactor feed consisted of 20 sccm of 100% CH4 and 1.0 mL/h of liquid H2O corresponding to an oxygen-to-carbon ratio of 2:1. Water was introduced via syringe pump to a preheater section consisting of SiC maintained around 200 °C by a Variac. Excess water was removed from the outlet stream by passing the effluent through a trap submerged in an ice bath. The dry product stream was characterized using gas chromatography (SRI 8610C). The reaction was conducted for

4 h before quenching in Ar. The catalysts were then removed for post-mortem analysis.

Section 5.2. Post-Reaction Characterizations of Spent Catalysts

Several post-reaction characterizations of the spent catalysts were conducted to compare the final state of both samples. These tests and their findings are outlined in the following subsections.

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Section 5.2.1. X-ray Diffraction

Both samples were analyzed using X-ray diffraction (XRD; Rigaku Miniflex 600) operated at 40 kV and 15 mA with a scanning rate of 1 °/min. As shown in Figure 5.2.1.1, the positive field sample oxidized to a much greater extent than the no-field sample.

Ni(111) Ni NiO NiO(200) Ag

NiO(111)

Ni(200)

Positive Field Intensity(a.u.)

No Applied Field 30 40 50 60 70 80 2q (deg.)

Figure 5.2.1.1. X-ray diffractograms of the post-reacted Ni catalyst samples with and without applied external power indicates extensive bulk NiO formation only when a positive field is applied.

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Section 5.2.2. Scanning Electron Microscopy Energy-Dispersive X-ray Imaging

The samples were imaged using scanning electron microscopy (SEM; FEI Quanta 200F) and SEM energy-dispersive X-ray spectroscopy (EDS; Tescan Vega3 with EDAX Element Silicon

Drift Detector EDS System). Example images are shown in Figures 5.2.2.1. No apparent coking is visible on the positive field sample whereas extensive coking is observed on the no-field sample from a cursory observation of both surfaces. The level of surface oxidation observed from the EDS imaging supports the XRD findings that the positive-field sample has oxidized.

Figure 5.2.2.1. SEM and SEM-EDS imaging of the post-reacted catalyst samples indicates a lesser degree of coke formation and a greater degree of surface oxidation in the sample subjected to a positive electrical bias.

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Section 5.2.3. Temperature-Programmed Oxidation

Both samples were burned in 5% O2/He while ramping the temperature at 10 °C/min to

800 °C in a temperature-programmed oxidation (TPO) test. The CO2 production was monitored using real-time gas analysis mass spectroscopy (Agilent 5953C). The results are presented as

Figure 5.2.3.1. CO2 signals peaked for the no-field sample at 360 and 605 °C while maximum CO2 production for the positive field sample occurred at 360 and 450 °C indicating that the samples consisted of different kinds of carbon. Moreover, the total amount of carbon burned from the no- field sample was 300% higher than the carbon burned off the positive field sample (189.25 vs.

63.06 μg C/g cat.).

0.4 360 450 605 Positive Field

No Field )

0.3

mol/min

(

2 0.2

0.1 FlowCO Rate

0.0 100 200 300 400 500 600 700 Temperature (°C)

Figure 5.2.3.1. TPO of the post-reaction samples indicates different types of carbon formation on the sample subjected to a positive electric field.

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Section 5.3. Discussion

Comparing the results for both the positive-field and no-field samples allows for several compelling conclusions to be drawn regarding the interaction of the chemical environment and the applied electric field. First, that coke production is clearly retarded in the presence of positive electric fields. No visible coke formation was apparent on the positive field sample by analysis of the SEM images. This corresponds well with the previous observation that only ~1.1% of the sample was C-C bonded carbon species from previous XPS analysis [2]. However, the positive field TPO signal was not zero. In fact, it contained nearly 33% of the total amount of carbon that the no-field sample did. Why is this carbon invisible to both the SEM and the XPS?

Comparing the location of the TPO peaks helps to clarify this situation. The positive-field sample consists of two peaks at 360 and 450 °C whereas the no-field sample has a small peak at

360 °C and a very large peak at 605 °C. This implies that the carbon deposits on the positive sample consist of less-stable carbon fragments that burn at lower temperatures.

This raises the question of what type of carbon material is produced in lieu of the presumed amorphous carbon (since no crystalline C signal is observed from XRD) on the positive field sample. We can look to previous computational predictions for guidance. According to the computational analysis, the change in energy barriers for successive abstraction of hydrogen atoms from methane follows the trend shown in Figure 5.3.1. These data, visualized from Che et al. [3], indicate that positive fields improve the ability of the catalyst to remove the first hydrogen from

CH4 while making further dehydrogenation more difficult. Hence, decomposition from CH3* to

C* is prevented. It is possible that the remaining surface C on the positive sample consists of

“activated” carbon fragments, i.e. CH3*, CH2*, and CH* that have been stabilized by the field,

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preventing their polymerization into coke. Since these species are much less stable than coke (i.e. graphitic or amorphous elemental carbon), they burn off at lower temperatures producing the low- temperature CO2 peaks observed by TPO.

0.15 CH* ® C* + H* 0.10

0.05 CH3* ® CH2* + H*

CH2* ® CH* + H* (eV)

a 0.00

E D -0.05

-0.10 CH4* ® CH3* + H* -0.15 1 2 3 4 H Abstracted

Figure 5.3.1. Changes in the activation energy of subsequent C-H scission events during methane decomposition on a Ni surface as determined by DFT analysis.

That the catalyst oxidized in the positive field is explained by two phenomena. First, as already mentioned, that water adsorbs more strongly to a surface with an applied positive field and second that oxygen tends to migrate into the Ni subsurface in the presence of positive surface fields.

Since stabilizing adsorbed water tends to make it less reactive, one might expect the two effects to nullify each other. Observation proves otherwise. To explain this finding, the dynamics of the bulk oxidation of Ni were studied using density functional theory (DFT). The details of this computational analysis are presented elsewhere [4]. According this analysis, presented in Figure

5.3.2, the movement of O* into the subsurface is facilitated by the presence of positive fields.

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Figure 5.3.2. DFT predictions for the various sub-processes involved in the oxidation of Ni by gas-phase water: (a) water adsorption to surface, (b) first deprotonation, (c) second deprotonation, and (d) oxygen surface-subsurface migration. This final step is visualized in (e) with a top-down view of the catalyst surface.

This movement into the catalyst bulk is ultimately responsible for the oxidation of the catalyst. Additionally, the removal of surface-adsorbed oxygen drives the water equilibrium point toward total decomposition despite stabilization of the water transition state (Figure 5.3.2.b and c). As discussed in Section 3.7, the balance between stabilizing forces and changes in rate and equilibrium due to changes in concentration is of utmost importance in determining the final outcome of the reaction. In the case of MSR, more complete DFT data are available for the various intermediates in the field and a general picture of the oxidation process can be postulated: (i) water molecules are stabilized in the positive field, leading to greater surface coverage of water on the catalyst but limiting its reaction; (ii) small amounts of O* are produced from the water layer coating the surface; (iii) these O* are destabilized by the field, driving them to react with CHx* fragments or enter the Ni lattice; (iv) scavenging of O* from C and Ni oxidation allow more O* to

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form to maintain dynamic equilibrium (Le Châtlier), further driving oxidation of the catalyst while maintaining a relatively C-free surface. The pathway to oxidation of the catalyst is summarized in

Figure 5.3.3. This is a simplified analysis compared to a complete microkinetic model which would also require the analysis of C oxidation which undoubtedly occurs and is responsible for maintaining the coke-free surface of the catalyst.

Figure 5.3.3. (a) Water is stabilized in a positive field, leading to greater surface coverage with a less-favorable orientation to the surface and a greater activation energy barrier toward deprotonation. (b) With its more favorable configuration and smaller barriers, a greater proportion of adsorbed water are deprotonated in the no-field case than in the applied field case, however, (c) a greater proportion of the oxygen adatoms produced in the positive field scenario enter the catalyst bulk, leading to much more rapid oxidation of the metal.

Section 5.4. Implications for MSR EFAC Processes

As discussed in Chapter 3, the effects of the applied field are multifaceted and can impact the behavior of systems in unexpected ways. Even when the general theory is very clearly outlined, the net effects of such tests can be difficult to predict. Although the surface fields generated in the reactor used in this study are “weak,” only on the order of 0.1 V/nm, they are enough to enhance configurational and transport phenomena during the reaction. This is most apparent in the analysis of the interaction between water and the catalyst, and how this leads to bulk oxidation of the

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catalyst over time. This has a knock-on effect of limiting coke formation in the reactor, though some of this observation may be attributed to stabilization of CH3* fragments on the catalyst surface. These are more akin to ions than complete molecules and are expected to be more susceptible to the field.

Although the catalyst will eventually deactivate due to oxidation rather than coke production, this is a step in the right direction. Severe coking can cause reactor blockages or, in the worst-case scenarios, reactor ruptures. Although oxidation of Ni catalysts may damage the catalyst itself [5], it can be reactivated via reduction in H2 and does not pose a threat to the reaction vessel itself.

As learned in Chapter 3 and reaffirmed here, it is not enough to analyze just one portion of a reaction when considering the effects of EFAC. Similarly, it is not enough to consider just the effects on the reaction when considering a larger reformer system. To begin to understand the wider ramifications of some of the process changes suggested in this work, we need a complete system model. Although a process model (e.g. using Aspen or Pro II) simulating the effects of an

EFAC reactor are not yet available, we can at least review the effects of changing process variables manually to begin to understand the effects an EFAC system might have.

De Falco et al. modeled an MSR process with a membrane separation system and found that changing individual reaction parameters (reaction temperature, CH4 flow rate, and steam-to- carbon ratio) had various knock-on effects throughout the entire process that can change the overall duty of the system [6]. Some of these findings are summarized in Table 5.4.1.

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Table 5.4.1. Effects on specific process heat duty (power required to produce one mole of pure H2) by changing reactor parameters. Summary of De Falco et al. [6].

Specific Duty Change Unit Change (kW Parameter (units) Initial Final (kW mol-1) mol-1 unit-1) Reaction Temperature (K) 673 873 -46.1 -0.23 Methane Flow Rate (kmol h-1) 2.0 7.0 172.0 34.4 Steam-to-carbon ratio (a.u.) 2.5 5.0 104.8 41.9 Reactor Pressure (bar) 10 30 -44.3 -2.22

This helps to shift our thinking from the reactor unit alone to the entire MSR process. For example, increasing the steam-to-carbon ratio improves the thermodynamics of the reaction by shifting equilibrium towards the products, but dilutes the hydrogen product making the separations unit (membrane diffusion) less efficient. In addition, more energy is required to boil the extra steam. The net effect is a very large increase in overall duty by changing the steam-to-carbon ratio.

Such holistic analyses are similar in spirit to the analysis of formic acid EFAC supplied in

Chapter 3. It is not good enough to consider only one portion of an entire process—both upstream and downstream variables may be affected. The work presented in this chapter suggests that applied positive fields can decrease steam requirements for a MSR process by enhancing water adsorption and limiting coke production. Increasing the temperature of the reactor also reduces the specific power requirements for the MSR system, and our previous work found that EFAC of MSR was more pronounced at higher temperatures [2]. Thus operating MSR as an EFAC system may represent a large energy savings compared to a standard MSR process.

Before EFAC can be considered for industrial processes, however, a practical design with high active area, high applied fields, and high pressures is needed. Can practical reactors be constructed which generate fields of sufficient strength to influence molecular orbitals directly?

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That is, can fields on the order of 1-10 V/nm be generated in high-pressure reactors for practical applications? Both questions are investigated in Chapter 6 using a nanosecond pulsed power coaxial capacitor reactor for logistic fuel reforming applications.

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CHAPTER 6: PULSED-FIELD CCR DESIGN AND TESTING

Improving the efficacy of electric field assisted chemical reactors requires new approaches.

As described in Chapter 2, the most promising designs for field-assisted chemistry are the integrated circuit reactor (ICR) and coaxial capacitor reactor (CCR) designs. Two variations of the

ICR design were investigated in Chapters 4 and 5 for different hydrogen-producing reforming reactions (formic acid decomposition and methane steam reforming). The major lesson from these studies has been that the field strengths associated are very small but can still affect the chemistry in significant ways. The only realistic way to improve ICR field strengths, however, is to increase the voltage applied to the system. Furthermore, the types of catalysts and total reactive area are severely restricted in ICR designs.

On the other hand, the CCR can accommodate a range of catalysts and is more easily scalable (by increasing length, e.g.). Additionally, the strength of the surface fields depends not only on the applied voltage but also on the reactor construction and design. As discussed in Section 2.4.1 the theoretical field strength at the catalyst surface in a CCR is readily modeled using elementary physics:

V 6.1 F = rκ ln(c⁄a) where κ is the relative permittivity of the material between the electrodes, V is the applied voltage, r is the location where the field strength is being calculated, and c and a are the radii of the outer and inner electrodes, respectively. In a real CCR, at least two dielectric layers will be present: the reactive gas flowing over one electrode and a layer of insulating material (e.g. quartz) to (i) prevent

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contact between the electrodes and (ii) suppress arc discharges. Example configurations are provided as Figure 6.1.

Figure 6.1. Two possible configurations for a CCR with the catalyst (a) serving as or coated on the outer electrode or (b) coated on the inner electrode.

Field strength near the catalyst surface for each of these designs depends on the applied voltage, the relative permittivity of the materials between the electrodes (κ푖), the radii of both the inner and outer electrodes, and the thickness of the dielectrics:

κ2V F1 = r(κ2 ln(b⁄a) + κ1 ln(c⁄b)) 6.2

κ1V F2 = r(κ2 ln(b⁄a) + κ1 ln(c⁄b))

Here, F1 is the field strength within the dielectric closest to the inner electrode and F2 is the field strength within the dielectric near the outer electrode; b is the radius of the boundary between the two electrodes (radius of the inner dielectric). The development of Equations 6.2 is

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provided as Appendix D. This physical analysis shows that CCR design involves the tuning of several geometric and physical parameters. Equations 6.2 were analyzed for the two different reactor designs shown in Figure 6.1. The results are provided in Figure 6.2.

Figure 6.2. Surface field strength in CCRs with different designs: (a) catalyst on a 7 mm ID outer electrode with a ceramic dielectric 0.5 mm thick on the inner electrode and (b) catalyst on the inner electrode with a quartz dielectric occupying half of the space between the two electrodes closest to the outer electrode (4.5 mm ID).

From this analysis we see that CCR design depends on several critical factors. First, the applied voltage has a strong effect on the resultant field strength as expected. Also expected is the increase in field strength gained by using two electrodes of similar size (smaller distance between electrodes)—both approaches require that the gap size be minimized as much as possible. With the specific geometric features of the two reactors in Figure 6.2 (their geometry is based on materials and techniques currently available), the catalyst as a CCR core design (CCRcore; catalyst on inside electrode) generates fields one order of magnitude stronger than the CCR shell design

(CCRshell; catalyst on outer electrode). This analysis does not imply that the CCRcore design is always superior to the CCRshell design in terms of field strength, as the geometry and physical properties of either reactor design can be changed. Neither does this analysis say anything about the functionality of the two designs as actual reactors. In fact, the CCRcore design should be expected to have substantially less active area per unit length than the CCRshell design. Of course,

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this can always be compensated for by increasing length or decreasing flow rate, but EFAC designers should be wary nevertheless. The CCRcore design was used for the work presented in this chapter.

Unlike the ICR design used in previous chapters, the presence of high surface electric fields in a CCR pose a serious danger of breakdown (plasma) generation as discussed in Section 2.4.2.

This is due to the proximity of the two oppositely charged electrodes. If the fields generated are too high, charge can travel through the dielectric, break down the reactive atmosphere, and induce plasma-activated chemistry. As noted in Section 2.4.2, the propagation of plasmas may be mitigated by introducing the potential as a rapid pulse rather than continuously. This tactic is implemented in the reactor design used for the work conducted in this chapter.

This chapter covers a range of brief studies undertaken using a CCR design using a catalyst consisting of Ni nanoparticles socketed in a LaCaTi perovskite. Section 6.1 details the catalyst preparation and Section 6.2 the reactor construction and experimental setup. These reactors were used to study a suite of different hydrogen-producing reforming reactions of increasing complexity: formic acid decomposition, n-dodecane steam reforming, isooctane steam reforming, and jet fuel steam reforming. The chemistry and relevance of these fuels are discussed in more detail in Appendix C. The results of these tests are presented in Section 6.3 and discussed in

Section 6.4. These data were collected in collaboration with the Naval Undersea Warfare Center

(NUWC) in Newport, RI and this chapter serves as an expansion of data reported in the Journal of

Power Sources.

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Section 6.1. Catalyst Preparation

The reactive catalyst core of each CCR reactor was fabricated using a modified version of the socketed Ni nanoparticles in perovskite reported by Neagu et al. [1] supported on a braided Ni wire. Preparation of the catalyst began by mixing Ni(NO3)∙6H2O, La2O3, CaCl2, and TiO2 powders together in an 11:97:49:100 ratio by mass. These powders were milled together, suspended in

EtOH by ultrasonication, dried, and finely ground together using an agate mortar and pestle. The powder was then calcined at 1100 °C for 20 h and finely ground again.

75 mg of powder was then added to a small beaker containing 40 mg of organic binder

(Heraeus) and mixed with acetone (1.5 mL) before sonicating to suspend the particles. This catalyst “ink” was then cast over a braided Ni wire support consisting of two lengths of Ni wire

(8” and 16”) twisted together such that one half was two wires braided together and the other half a single wire. The single-wire half was used to connect to the power source and was left unaltered.

The catalyst ink was passed dropwise over the braided portion of this Ni wire support using a pipette. Several seconds were allowed to pass between drops to allow the acetone to evaporate. As the acetone evaporates, the binder-coated particles are left on the wire surface. Approximately 40 mg of catalyst precursor was loaded onto the support. After drying in air at room temperature, the catalyst rods were reduced at 900 °C for 12 h in flowing 5% H2/Ar. SEM images of the catalyst and particle size distributions for a new catalyst versus one maintained at 700 °C for 500 h are shown in Figure 6.1.1. The slight increase in the distribution tail is attributed to further growth of the particles from remaining Ni in the support rather than agglomeration or sintering of pre- existing particles since the distribution did not move, but only changed from normal to log-normal.

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Figure 6.1.1. (a) Socketed Ni nanoparticles in a LaCaTi perovskite support and (b) its particle size distribution before and after treatment at 700 °C for 500 h.

Section 6.2. Experimental Setup

Reactors were fabricated inside quartz tubes (7 mm ID). The outer electrode consisted of a stainless steel tube (4.5 mm ID, 20 cm long) connected by a Ag wire to the power source via slits cut into the sides of the tube and sealed with ceramic paste (Aremco 552). The catalyst core (~1 mm OD) was inserted into the outer electrode through a quartz thermocouple sheath that served to prevent contact between the electrodes and as a dielectric barrier. Reactor temperatures were controlled externally using a tube furnace (Lindberg/Blue).

Fuels for each reaction were distributed to the reactor by bubbling Ar through the liquid fuel. In the case of steam reforming reactions, Ar was also bubbled through water. Specific flow rates and concentrations for each fuel are provided in Sections 6.2.1-6.2.3.

Gas composition was monitored using real-time gas analysis mass spectroscopy. For long- term tests, both the inlet and outlet streams were sampled alternatively in 3 minute cycles. Only the reactor outlet was monitored, sampled every 5 s, for temperature-programmed tests (TPRxn).

Each reaction was tested with and without applied fields of the direction predicted to increase performance, specified in Sections 6.2.1-6.2.3. Power was supplied using a low-power

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nanosecond pulser from Eagle Harbor Technologies. The pulser was operated at 3 kV and 50 kHz with 200 ns duration pulses for all tests.

Section 6.2.1. Formic Acid Decomposition

For all formic acid decomposition tests, Ar was bubbled through a liquid reservoir of

HCOOH maintained at 0 °C using an ice bath. Weight hourly space velocities (WHSV) of 120 h-

1 were used for all tests. TPRxn tests were conducted using a ramp rate of 10 °C/min to 400 °C.

Long-term tests were conducted with the furnace maintained at 300 °C for a total of 4 h. The inner electrode (catalytic surface) was maintained at a negative potential for applied-field tests.

Section 6.2.2. Hydrocarbon Steam Reforming

During the hydrocarbon steam reforming tests, Ar was bubbled through two liquid reservoirs in parallel: one containing water and one containing n-dodecane (a diesel simulant), isooctane (a gasoline simulant), or JP-10 (a specialty jet fuel).

JP-10 consists primarily of a tricyclic alkene with the systematic name tricyclo[5.2.1.02,6]decane and the common name tetrahydrodicyclopentadiene. Roughly 96.5% of the JP-10 mixture exists as the exo isomer of this compound, with the balance consisting of the endo conformer (2.5%) and adamantine (1.0%) [2]. The structure of this compound is provided in

Figure 6.2.2.1.

Figure 6.2.2.1. Structure of tricyclo[5.2.1.02,6]decane (JP-10) as a (a) ball-and-stick model and (b) line structure.

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The flow rates to each bubbler were balanced such that the final reaction mixture consisted of water and fuel with an oxygen-to-carbon (O/C) ratio of 2. Both bubblers were maintained at room temperature around 23 °C. The flow rate to each bubbler was determined using the following set of equations:

−1 Mfuel V̇Ar,fuel = V̇total(1 − Mfuel) (1 + R ) 6.2.2.1 MH2O

1 M −1 ̇ ̇ H2O 6.2.2.2 VAr,H2O = Vtotal(1 − MH2O) (1 + ) R Mfuel

where V̇Ar,푖 is the volumetric flow rate of Ar through the bubbler containing species i; V̇total is the total desired flow rate; R is the desired oxygen-to-carbon ratio; and M푖 is the concentration of species i in the stream, as determined by the Antoine coefficients for the material (A, B, and C), the bubbler temperature (T), and ambient pressure (P):

B 1 (A− ) M = 10 C+T 6.2.2.3 푖 P

Antoine parameters for various temperature ranges are available from NIST and in many standard thermodynamics references and texts. Experimental Antoine parameters for JP-10 were reported by Han et al. in 2006 [3]. WHSV of 120 h-1 were again used for all tests.

Section 6.3. Results

Test results for each of the fuels are presented in Sections 6.3.1-6.3.4. Formic acid is first used to estimate the field strength using the technique developed in Chapter 4, then each of the heavy hydrocarbon fuels are investigated separately.

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Section 6.3.1. Formic Acid

Selectivity data for formic acid decomposition within the CCR reactor under no-field and negative field conditions are provided as Figure 6.3.1. Neither CO2 nor CO calibration gases were on hand to allow for the computation of real selectivity values. Hence, only the raw signals are reported. However, the field strength approximation method presented in Chapter 4 (Equation

4.2.3.2) depends only on the ratio of selectivities. Hence, the calibration parameters (linear with intercepts at zero) will divide out. The only information that is lost by being unable to calibrate are the true selectivity values for formic acid decomposition over the Ni perovskite catalyst, which is

irrelevant to the study of logistic fuel reforming that is the main focus of this work.

/CO Selectivity (a.u.) Selectivity /CO

2 CO

Negative No Field

Figure 6.3.1. CO2/CO signal ratios for Ni perovskite CCR under no-field and negative field conditions. The ratio between these signals is used in conjunction with Equation 4.2.3.2 to determine the average field strength supplied by the reactor.

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Section 6.3.2. n-Dodecane

General reaction data for n-dodecane steam reforming are presented in Figure 6.3.2.1.

Figure 6.3.2.1. Various reaction characterization parameters for n-dodecane steam reforming at 700 °C in a CCR with a Ni perovskite core under high frequency pulses. (a) Onset temperature for H2 production, n-dodecane consumption, and H2O consumption. (b) H2 production rates. (c) Catalyst deactivation rates. (d) Average CO2 and CO signals. (e) H2 yield, n-dodecane conversion, and H2O conversion.

Section 6.3.3. Isooctane

General reaction data for isooctane steam reforming are presented in Figure 6.3.3.1.

Figure 6.3.3.1. Various reaction characterization parameters for isooctane steam reforming at 700 °C in a CCR with a Ni perovskite core under high frequency pulses. (a) Onset temperature for H2 production, isooctane consumption, and H2O consumption. (b) H2 production rates. (c) Catalyst deactivation rates. (d) Average CO2 and CO signals. (e) H2 yield, isooctane conversion, and H2O conversion.

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Section 6.3.4. JP-10

General reaction data for JP-10 steam reforming are presented in Figure 6.3.4.1.

Figure 6.3.4.1. Various reaction characterization parameters for JP-10 steam reforming at 700 °C in a CCR with a Ni perovskite core under high frequency pulses. (a) Onset temperature for H2 production, JP-10 consumption, and H2O consumption. (b) H2 production rates. (c) Catalyst deactivation rates. (d) Average CO2 and CO signals. (e) H2 yield, JP-10 conversion, and H2O conversion.

Section 6.4: Discussion

Conducting a field estimation computation using the process developed in Chapter 4 on the formic acid decomposition data presented in Figure 6.3.1 yields an average surface field strength of 0.16 V/nm. This average field strength is in the same ballpark as the estimated field strength for the ICR used in Chapter 4.

Additionally considering the complexity of the switching applied field, however, it may be useful to compute the maximum field strength delivered during operation of the pulse power system. An example square wave of the type generated by the pulser is depicted in Figure 6.4.1.

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f -1

Fmax

F Field Strength Field (a.u.)

w Time (a.u.)

Figure 6.4.1. An example of a square wave of the type produced by the nanosecond pulser. F̅ and Fmax are the average and maximum field generated, respectively; w is the width of a single pulse; and f is the frequency of the pulses.

Because the field switches on and off, the average produced field will be smaller than the maximum applied field. The average field strength, which was estimated from the formic acid experiment, can be computed by averaging the square waveform (F(t)):

1 T F̅ = ∫ F(t)dt 6.4.1 T 0 where t is general time and T is the time interval of interest. The square wave can be easily integrated by summing the rectangles defined by the pulse parameters:

T n ∫ F(t)dt = ∑ wFmax = nwFmax = fTwFmax 6.4.2 0 i=0 where n is the number of pulses delivered during time T. Thus, the maximum field strength can be estimated:

F̅ F = 6.4.3 max fw

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V When Equation 6.4.3 is evaluated using the experimental parameters (F̅ = −0.16 , 푓 = nm

50000, and w = 200 ns), the resulting maximum field strength is -16.4 V/nm.

Moreover, estimating the average surface field strength using the CCR physics of Equation

6.2, the approximate maximum surface field strength for this design consisting of a catalyst-coated wire core ~1 mm in diameter and a 4.5 mm ID SS tube as the outer electrode with 3.0 kV applied will be ~0.0053 V/nm. Equation 6.4.3 can be used in reverse to compute the predicted average field strength that should have been observed by the formic acid probe method: ~3.4x10-5 V/nm.

These numbers are summarized as Table 6.4.1. The actual predicted value for this reactor lies somewhere between the Ar and quartz predictions, as the CCR contains a quartz dielectric with empty space for Ar gas flow (and other reactants and products).

Table 6.4.1. Surface electric field estimates for the CCR design used in this study, in V/nm, from both first-principles predictions as well as formic acid probe measurements.

Predicted Measured Average 0.000053 0.16 Maximum 0.005328 16.4

Much like the COMSOL model used in Chapter 4 to estimate surface field strengths in an

ICR over Ni foam, this prediction is several orders of magnitude lower than the formic acid measurements suggest. The discrepancy is again attributed to field enhancement effects at the surface, particularly at active sites where catalysis occurs: bumps, edges, defects, kinks, and so forth.

Although this estimate for the maximum field generated at the active sites is within the correct order of magnitude for molecular orbital distortion (1-10 V/nm), the average field is not.

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The question arises as to how exactly the field interacts with the reactive environment to produce the observed changes. Clearly, since the field is not continuous throughout the test period, some mixture of effects can be expected. In particular, the field switches from on to off rather than from positive to negative as might be expected with an alternating current source. Hence, a mixture of field and no-field effects are expected, rather than a mixture of positive and negative field effects.

Because of these complex interactions, explaining the (sometimes contradictory) observations for each of the fuels from first principles is difficult.

It is particularly interesting that the n-dodecane data does not follow the same apparent trend in reactivity as isooctane and JP-10. For example, the application of a positive electric field apparently decreases the water reaction onset temperature during n-dodecane steam reforming while increasing the water reaction onset temperature during both isooctane and JP-10 steam reforming. While this may be experimental error due to equipment limitations (for example, the concentration of n-dodecane (~0.01%) was an order of magnitude smaller than that of JP-10

(~0.28%) and two orders of magnitude smaller than that of isooctane (~2.5%) due to the inability to heat the fuel bubbler), it may also be attributable to differences in the chemistry. Both isooctane and JP-10 are heavily branched hydrocarbons and may behave differently than n-dodecane in the presence of the field. Much more work needs to be done, both experimentally and computationally, to investigate these data—both to confirm the findings and rule out experimental error as well as to find possible explanations for the observed differences in reactivity trends.

That said, the more complete JP-10 data set seems encouraging. Although it is a much more complex hydrocarbon than methane (which was investigated in Chapter 5), there are several points of overlap. As one example, the reactivity of water is strongly affected by the presence of the field:

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water is able to react at a much lower temperature in the applied negative field than in the applied positive field. This is attributed to the stabilization of the H2O* intermediate (in the positive field) and the increase in the frequency factor due to appropriate orientation of the water molecule with respect to the surface (in the negative field) as discussed in Chapter 5. On the other hand, the total conversion of water is increased under the effects of a positive field and decreased with an applied negative field. This again follows from the investigations presented in Chapter 5 which indicates a greater propensity for water adsorption and, over time, a shift toward the production of O* in the

Ni subsurface. The expected oxidation, and deactivation, of the catalyst due to the production of these O* groups was not apparent from the deactivation data, and more investigations are still needed to determine the extent of oxidation of the perovskite catalyst within a pulsed field. If extensive oxidation does not occur, this may be attributed to relaxation periods wherein the pulsed field is switched off, which may free the O* groups to react with surface carbons to produce CO or CO2. In fact, this may be why the production rate of CO2 in the positive field is so much higher than in the no-field scenario, as O* is produced and “stored” in the catalyst for the duration of the positive pulse, then released during the relaxation period all at once. The pulsed field in this case may act to concentrate O* and then release it in bursts.

Like methane steam reforming, the hydrogen yield did not appreciably increase during JP-

10 reforming. However, since both H2O and JP-10 conversion increased, the total hydrogen production rate was significantly higher in the applied positive field than without an applied field.

This fact, combined with the drastically reduced deactivation rate of the catalyst, makes the technique a promising one for a field-assisted hydrogen production unit.

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Moreover, since time allowed for the full investigation of both applied field directions for the JP-10 fuel, some interesting trends can be teased out from the data that are not possible with either the isooctane or n-dodecane data. Stoichiometry for the full steam reforming of JP-10:

C10H16 + 20 H2O ⟶ 28 H2 + 10 CO2 6.4.1 and Equation 1.4.3 can be used to estimate the maximum change in Gibbs energy of the steam reforming reaction in the presence of the fields estimated by the formic acid tests (the measured maximum field strength of 16.4 V/nm were used for these computations). When the reaction data are plotted against this energy change, the curves presented in Figure 6.4.2 are obtained.

Coefficients of determination range from 0.8503 (for H2 yield) to 0.9992 (for average H2 production rate) indicating a very strong correlation with the predicted change in Gibbs energy as a result of the applied field.

Figure 6.4.2. JP-10 steam reforming at 700 °C within a CCR with a Ni perovskite core subjected to high frequency pulses. (a) H2 yield, JP-10 conversion, and H2O conversion. (b) Initial and average H2 production rates.

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Despite these interesting trends, much more work is still needed before this technology can be implemented by engineers or before it can be fully understood by scientists. Not only must the overall chemistry be considered (as has been done throughout this dissertation using thermodynamic and kinetic arguments) but the effects of strong fields on the catalyst surface itself are also important. As discussed in Chapter 5, the surface can become oxidized due to the presence of the field, causing cracking and pitting due to expansion of the lattice and ductility losses. Pulsed fields have also been shown to have significant effects on metal surface structures, causing not only the migration of ions but also of surface defects [4]. Strong fields are even known to cause the wholesale restructuring of particles by field evaporation [5]. These complex interlocking phenomena make EFAC a difficult nut to crack which will require many more years of deep study and creative experimental design before the leap from pure to applied science can be successfully made. Chapter 7 details some suggested pathways for future researchers to continue this work and develop the field-assisted fuel reformer from both a purely scientific as well as an applied engineering perspective.

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CHAPTER 7: FUTURE DEVELOPMENTS

The work presented in this dissertation has provided some promising evidence for the use of electric field assisted catalysis (EFAC) as a reaction engineering tool. Moreover, techniques have been developed for the characterization of EFAC-based reactors which remove some of the guesswork involved in their design. Several designs have been proposed and tested, along with their physical operating principles. Finally, some detailed computational work has been developed including both Monte Carlo and density functional theory (DFT) models to supplement and support the experimental evidence.

However, the development of this technology from both pure and applied points of view still has a long way to go. There is an argument to be made that the EFAC phenomenon is, at this point, fairly well-understood from a purely scientific point of view. From revelations of its importance in naturally occurring catalytic systems such as enzymes and zeolites to high-field in vacuo studies using the field ion and scanning tunneling microscopes to more modern detailed

DFT studies—there is little doubt from a scientific perspective that the enhancement of chemical reactivity is, in principle, possible.

The successful transition from pure to applied science, however, has still not been made. It is hoped that the work and arguments presented in this dissertation will provide guidance for those working on this problem in the future. Clearly, the problem is not a trivial one. Not only are there significant roadblocks presented by the inherent physics of the system (such as achieving sufficient field strengths in the first place; much less doing so without producing discharge), but our understanding of the fundamentals of the effect are not sufficiently advanced or detailed enough to enable accurate predictions of the effects of an applied electric field in a timely manner.

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The work presented in this dissertation has so far made progress on both fronts: new reactor designs have been presented and tested which apparently achieve sufficiently high surface fields without the production of discharges or Joule heating, and some detailed analysis has provided insight into portions of the hydrogen producing reactions which allow for a handful of predictions to be made with some accuracy.

Clearly, however, there is much more work to be done. This chapter outlines several ideas for future researchers to not only continue the work presented in this dissertation, but to take EFAC studies in slightly different directions. Section 7.1 expands upon the work presented in Chapter 6 with suggestions for a more detailed analysis of logistic fuel reforming. Section 7.2 presents an idea for investigating the effect of branching in long-chain hydrocarbons and their interactions with the applied field. Suggestions for the study of field structure including pulse frequency, duration, and intensity are outlined in Section 7.3. Section 7.4 describes an experimental approach to testing the effects of sulfur poisoning on the catalyst and how this might be mitigated by an applied field. The need for a complete economic analysis of a proposed EFAC unit is outlined in

Section 7.5. A handful of other potentially interesting and topical hydrogen-producing reactions are described in Section 7.6, and finally, Section 7.7 calls for detailed DFT analysis of the formic acid decomposition reaction.

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Section 7.1. Detailed Investigations of Logistic Fuel Reforming

The isooctane and n-dodecane tests presented in Chapter 6 represent only preliminary data collected quickly before the detailed JP-10 study was conducted. Proper attention should be given to these compounds since they are frequently used as models for gasoline and diesel, respectively—both important logistic fuels. These fuels were included in the research presented in

Chapter 6 due to their importance in the Navy, but more focus was given to JP-10 due to its limited availability outside of the NUWC facility.

Section 7.2. Hydrocarbon Structural Considerations

One possible explanation for the puzzling and inconsistent trends observed in Chapter 6 with the isooctane, n-dodecane, and JP-10 data is their structural differences. If the data can be validated via the more detailed experiments suggested in Section 7.1, then the effect of branching on hydrocarbons in the field can additionally be studied. Even if the preliminary data in Chapter 6 turns out to be incorrect (due to experimental error, lack of sufficient replicates, etc.), then any trend that does emerge may still benefit from an analysis of hydrocarbon structure. For one thing, the polarizability of the alkanes depends almost exclusively on the total number of bonds in the structure as shown in Figure 7.2.1. This is to be expected, as the polarizability is a function of the total number of electrons and their binding strength to their nuclei—hence the types of carbons

(primary versus tertiary, for example) or overall structure (straight-chain versus branched or ring) has little effect [1, 2]. Moreover, the dipole moment of all saturated aliphatic alkanes is nearly zero due to the low electronegativity difference between carbon and hydrogen and structural symmetry.

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Figure 7.2.1. The polarizability of saturated aliphatic alkanes depends only on the total number of bonds, not on the overall structure of the molecule. Data taken from online physical properties databases such as the CRC Handbook, NIST, and ChemSpider.

Based on these physical attributes, one might expect all alkanes to behave similarly in the presence of applied electric fields; perhaps only reacting to greater or lesser extents. However, if the isooctane and n-dodecane data presented in Chapter 6 are accurate, this is clearly not a correct assumption. In that case, the major difference must come from the transition states or decomposition products of the alkanes as they break down over the catalyst surface. While one might again expect significant overlap in this regard—for example, methyl fragments are surely produced during the fragmentation of most or all alkanes—other intermediates may arise that are not consistent across all alkanes. For example, branched alkanes may produce a greater number of methyl fragments as their branches break off—but they may also be more susceptible to the formation of tert-butyl fragments that can be stabilized by the field. Cyclic compounds may give rise to benzene precursors or other cyclic alkenes like cyclopentadiene. Each of these intermediates, transition states, or fragments may be influenced by the applied field in contradictory ways as dipole moments and π-bonds form.

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To study these effects, detailed density functional theory analysis could be conducted. This may get complicated quickly, however, as the alkane structures become more complex. Modelling

JP-10, for example, may still be too computationally expensive.

An experimental approach is therefore, at least initially, advised. By testing a number of different compounds in the same manner as the isooctane, n-dodecane, and JP-10 were tested, the relationship between structure and field may be teased out. Examples of readily available compounds are provided in Table 7.2.1.

Table 7.2.1. Examples of commercially available aliphatic alkanes in a variety of configurations for testing structural effects on EFAC steam reforming.

Straight-Chain Branched Cyclic Pentane Isobutane Cyclopentane Hexane 2-methylpentane Cyclohexane Nonane 2,3-dimethylbutane Cyclooctane

Section 7.3. Electric Field Structure and Impact on EFAC

Another important question that arises when contemplating the experiments presented in this dissertation relates to the structure of the electric field itself. Tests in Chapters 4 and 5 used constant fields of a singular direction whereas the tests in Chapter 6 used a pulsing field of a singular direction. Several questions present themselves:

1. Can a CCR be operated without dielectric breakdown at sufficiently high field strengths for observable effects using a constant-voltage source? 2. What is the impact of pulse duration on EFAC? 3. What is the impact of pulse frequency on EFAC? 4. What is the impact of pulse intensity on EFAC? 5. Will an alternating electric field have a measurable impact on EFAC?

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The first question can be easily investigated by using a power source of sufficiently high strength. According to the data plotted in Figure 6.1, a power source capable of delivering several kilovolts of potential to the CCR should theoretically be able to generate sufficient field strengths after accounting for field enhancement factors. Mitigating plasma generation will be substantially more difficult, however. Adding stronger dielectric barriers, increasing the gas flow rate, or adding quenching species like sulfur hexafluoride may help.

Answering questions 2-4 will require substantial time and careful experimental planning, as the influence of three interacting variables must be teased out. A systematic or complete approach to this test would require an extraordinary amount of tests. Even selecting just four levels for each of the three parameters would require at a minimum 64 tests to be conducted to investigate each combination of factors. Using only a threefold replicate, a minimum of 192 tests would be required. Allowing for equipment malfunctions, routine maintenance, equipment time needed for other crucial tests, and other researcher obligations, this “simple” experiment could easily take several years.

Instead, a statistical approach known as the Latin Square experimental design should be used for this test. The details of such a design are readily available on the internet as well as in any good statistical methods textbook. As such, they will not be explained in detail here except to say that an example of one way to approach this experiment using only 16 trials (48 with three replicates) is outlined in Figure 7.3.1. Preliminary results for such a test could be completed in a matter of a month. Using this method, two parameters are varied at the same time. For example, the first four tests would use pulse parameters of (w, f, h) = (200, 5, 2.5), (200, 20, 4.0), (200, 35,

2.0), and (200, 50, 1.5). Well-developed statistical methods can then determine the impact of each

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of these variables on the EFAC of a given fuel. When these data are obtained, the relationship between EFAC and the duty cycle (percent time the field is “on”) of the pulser should be analyzed.

For example, the duty cycle of the settings used for the work presented in Chapter 6 was 1% (200 ns pulses 50,000 times per second means the field was only ever “on” for 1% of the total run time).

Does decreasing this cycle to 0.5% cut the observed effects in half?

Figure 7.3.1. Parameters for the 16 experiments required to test the effects of pulse height (voltage), pulse width, and pulse frequency on EFAC.

Question 5 may be similarly difficult to answer, though two possible routes are apparent.

Of course an experimental approach requires only the substitution of the DC or pulse source with an AC source. Determining the frequency and magnitude parameters and their relationship to

EFAC phenomena may require in-depth study as already described for the pulse source.

Computational support using DFT models will be difficult if not impossible for an alternating field. However, some interesting models could possibly be constructed by taking a

Monte Carlo style approach. Using the DFT data from steady-field analysis, a model could be constructed in which the field is continuously modulated as with an AC source during the

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simulation. This would only necessitate using a lookup table for activation energy and frequency factor values as the field changes, though a complete microkinetic model (i.e. the entire mechanism) will need to be known to construct such a model.

Section 7.4. Prevention of Sulfur Poisoning using Applied Electric Fields

Real fuels, unlike the model fuels used in the laboratory, invariably contain traces of sulfur- containing compounds from their time underground. This sulfur can cause significant problems in reforming units, as the catalysts needed for fuel reforming are generally quite susceptible to sulfur.

Over time, the catalyst can deactivate not just from coke formation, but also from sulfur poisoning.

It is therefore of general interest to study sulfur poisoning during EFAC.

Predicting the behavior of sulfur-containing compounds (SCCs) during EFAC is difficult, as the exact structure and concentration of said compounds varies depending on the source and age of the petroleum product [3]. In fact, identifying exactly which SCCs are present in a given sample of petroleum products is a non-trivial endeavor [4]. However, SCCs can be classified by functional group into six broad categories: hydrogen sulfide (H2S); elemental sulfur (S); thiols or mercaptans

(R-SH); sulfides (R1-S-R2); polysulfides (R1-S-…-S-R2); and thiophenes. Although H2S and S are both frequently present in the crude oil reservoir, they are more readily separated and are less frequently present in the final product than the other categories. However, the reaction of organic

SCCs with high-temperature water (as in steam reforming conditions) results in their decomposition into H2S [5]. It is likely, then, that H2S is the compound directly responsible for poisoning of the catalyst. Two possible experimental procedures present themselves: first, the direct use of H2S as a stand-in for possible degradation products from SCCs in the fuel; and second, the use of a model SCC such as benzothiophene which can be added to the fuel during reaction.

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The former experiment is much easier to analyze from an EFAC perspective due to the structural similarity of H2S to H2O and the similarities between the Ni-S and Ni-O bonds [6]. In this regard, the analysis developed in Chapter 5 is directly applicable with one exception—the larger atomic radius of S (almost double that of O) will make the movement of S* into the subsurface extremely difficult, even with the aid of an electric field. Hence, the expected outcome is that a positive field should improve Ni-SH2 bonding but discourage the S-H scission that leads to poisoning S. Since the S* to S*subsurface transition is likely unfavorable, the Ni catalyst should not sulfurize due to H2S as it oxidizes due to H2O. Many H2S molecules, then, should escape the reactor without poisoning the surface—especially if a pulsing positive field is used to release the surface-bound H2S periodically. On the other hand, a negative field should encourage S production and enhance surface poisoning. Of course, this off-hand speculation can only be taken so far.

Detailed DFT studies and experimental investigations are still needed to confirm these conjectures and rule out any unexpected side-reactions.

The model SCC study (e.g. using benzothiophene), while less readily predictable, has a somewhat closer connection to reality since an actual organosulfur compound is used. Might the presence of an applied field discourage dissociation into the H2S poison in the first place, thereby adding another layer of protection on top of those already discussed? This is impossible to predict with crude analysis, and may even be too difficult with a DFT model. Hence, it may be well worth devoting experimental time to investigating.

Section 7.5. Economic Advantages to an EFAC System

One frequently asked question, especially amongst engineering circles, relates to the economic advantages afforded by an EFAC system. Until recently, EFAC systems were too poorly

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understood to even begin to hazard a guess at such a question. With the work presented in this dissertation, however, one begins to see a path for the construction of large-scale commercial or industrial CCRs for EFAC steam reforming of hydrocarbons. These CCRs, with their well-defined power draws and our increasing understanding of hydrogen yield improvements and catalyst lifetime extension due to the applied field, are ideal candidates for a comprehensive large-scale economic analysis. Such an analysis should take into account the reduction in steam ratios needed to maintain catalyst integrity over long periods of time (reducing steam requirements by half or more), reduced reaction temperatures, increased hydrogen yields, reduced CO generation, and the energy costs for operating the pulser compared to the savings from making these changes. Simple back-of-the-envelope computations have been attempted in the past for an ICR for the EFAC of methane steam reforming, but these involved only an analysis of the steam reduction requirement and did not find use outside of a few conference presentations as order-of-magnitude approximations.

Section 7.6. Other Applications for EFAC

Obviously, a great many chemical processes could potentially be impacted by EFAC—too numerous to list. Within the scope of hydrogen-producing reactions which have been analyzed in this dissertation, however, a handful of additional reactions come to mind: ammonia reforming

(Section 7.6.1), ethanol reforming (Section 7.6.2), and biogas reforming (Section 7.6.3). A brief description of the importance of each of these reactions and some possible benefits from the applied field are provided in each of these subsections.

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Section 7.6.1. Methanol Reforming

Methanol is a direct competitor for intermittent hydrogen storage technology. Methanol has several possible reactive pathways, as discussed in detail in Appendix B, but the most likely commercially important ones are partial oxidation and steam reforming. The former is more promising for transportation applications because it does not require the user to carry additional weight (the oxidant being liquid water), but the latter should be more susceptible to EFAC conditions due to the presence of water (which has a permanent dipole moment). Methanol steam reforming occurs at low temperatures compared to hydrocarbon fuels, between 200 and 300 °C

[7]. An analysis using the Bergmann equation indicates that a negative electric field should improve the thermodynamics of this reaction as shown in Figure 7.6.1.1.

Figure 7.6.1.1. Thermodynamic analysis of the methanol steam reforming reaction indicates that a negative field should increase the equilibrium constant by almost an order of magnitude in a field of 1 V/nm.

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Section 7.6.2. Ammonia Reforming

Ammonia, like formic acid and methanol, has been identified as a possible “indirect hydrogen storage material” and is the topic of much research along the same lines as both formic acid and methanol [8]. Unlike formic acid and methanol, however, the ammonia-producing reaction:

N2 + 3H2 ⟶ 2NH3 7.6.2.1 is extremely thermodynamically favorable, only limited by kinetics. Ammonia production is, of course, an extremely well-studied reaction and involves perhaps the most famous chemical production process in history: the Haber-Bosch process. This process was chiefly developed to overcome the kinetic limitations of Reaction 7.6.1.1 using standard catalytic techniques. The reaction is operated at high temperatures and pressures over an iron catalyst.

The reverse reaction, ammonia reforming, therefore, can be expected to be an extremely thermodynamically unfavorable reaction. The reaction is, moreover, capable of turning liquid ammonia into hydrogen and nitrogen: a useful prospect for CO-sensitive proton exchange membrane fuel cells. Ammonia is therefore promising for H2 storage and transportation—the key hurdle being releasing that H2 in situ and on-demand.

Because the reverse of Reaction 7.6.2.1 is thermodynamically limited, it may be possible to improve H2 production by the application of an applied electric field in an entirely predictable

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manner using Equation 1.4.2. EFAC may therefore prove a useful tool in the advancement of this promising technology and should be investigated further.

Section 7.6.3. Ethanol Reforming

Much interest has been shown in the use of ethanol as a biofuel, and in the steam reforming of ethanol for the operation of various types of fuel cells in recent decades [9]. The reaction is complex and involves a number of side-products including syngas genesis:

CH3CH2OH + H2O ⟶ 2 CO + 4 H2 7.6.3.1

In a way, the use of ethanol as a hydrogen carrier is identical to the proposed uses of formic acid, methanol, and ammonia for the same use. One major point of difference is, however, the material source. Where formic acid, methanol, and ammonia are all proposed to be produced directly from H2 and then converted back into H2 in situ, ethanol is instead proposed to be produced from biological sources including agricultural waste products or even directly from crops like corn or soybeans [10, 11]. This is sometimes termed bioethanol. Although there is some debate over the feasibility and ethics of converting food crops into fuel, or using land that could be used to grow food to grow fuel crops instead, biofuels are still an ongoing area of research and government investment worldwide, and will almost assuredly comprise some not-insignificant portion of the world’s future energy portfolio [12-14].

Hence, there are many opportunities for investigations into the use of EFAC for ethanol reforming systems. The multiple side reactions, intermediates, and possible byproducts of ethanol reforming make it difficult to analyze without direct DFT computation. However, the molecule is small enough that a comprehensive DFT model with a corresponding microkinetic analysis could

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be feasibly conducted by a dedicated researcher. An experimental approach would also be beneficial, and should be straightforward to attempt, if not to predict.

Section 7.6.4. Biogas Reforming

The complex mixture of CH4, CO2, H2S, NH3, H2, N2, O2, and H2O resulting from the bacterial breakdown of waste from human activities, known as biogas, has long been the subject of investigation for its uses in energy production. Among these investigations, many researchers have sought methods for H2 production from biogas for fuel cell applications [15, 16]. Although comprised chiefly of CH4 (55-70%) and CO2 (30-45%), the trace elements present in real biogas may have a substantial impact on the EFAC-induced chemistry of the reactions.

Steam reforming and dry reforming of biogas are both among the processes used for upgrading the material to hydrogen gas. This may then represent a natural next step to continue the work presented in Chapter 5, albeit with a somewhat more complex and realistic gas mixture.

Initial research should begin with a simple mixture of CH4, CO2, and H2O to elucidate how the

EFAC steam reforming of CH4 is influenced by the presence of CO2.

Section 7.7. Detailed Microkinetic Studies of the EFAC of Formic Acid

Although some significant progress was made towards the understanding of the thermodynamic changes wrought by the application of electric fields, a detailed kinetic study would go a long way toward painting a complete picture. The formic acid molecule itself is relatively simple, and its overall reactions seemingly straightforward, but the complete picture (as discussed in Chapter 3) may be more complex than many theorists first understood. The mechanism presented in Chapter 3 suggests that complex gas-adsorbate interactions may be partially responsible for the activity of formic acid on a Mo2C surface, as much as adsorbate-

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surface interactions and gas-surface interactions. Unfortunately, gas-adsorbate interactions are rarely studied using traditional DFT analyses unless they are already suspected to contribute substantially to the reaction. For example, a complete microkinetic study of catalytic formic acid decomposition over Au catalysts showed no indication of possible gas-adsorbate interactions [17].

However, the researchers were investigating a catalyst that showed zero activity toward dehydration and had no reason to suspect such interactions nor to create model scenarios where such an interaction could occur. Such a microkinetic analysis over Mo2C or Ni would prove invaluable to not only provide support to the conjectured mechanisms of Chapter 3, but to refine the formic acid probe methods for measuring field strength developed in Chapter 4.

Section 7.8. Cross-validation of Reactors

Repeating experiments conducted in the integrated circuit reactor (ICR) in the newer coaxial capacitor reactor (CCR) can help to validate the operation of the CCR and help to answer the question of the relative field strength in the CCR design compared to older designs. Since many experiments on methane steam reforming have been conducted in the ICR design, it may be valuable to repeat these tests in a CCR design for comparison. Alternatively or additionally, other reactions can be selected (e.g. those suggested in Section 7.6) to run over both designs independently. This would not only cross-validate the reactors and help to expose any flaws in their design, but also provide additional examples of EFAC reactions.

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113. Jefimenko, O., Demonstration of the Electric Fields of Current-Carrying Conductors. American Journal of Physics 1962, 30 (1), 19-21.

114. Preyer, N. W., Surface charges and fields of simple circuits. Am. J. Phys. 2000, 68(11), 1002-1006.

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Chapter 3

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6. Bandara, A.; Kubota, J.; Onda, K.; Wada, A.; Kano, S. S.; Domen, K.; Hirose, C., Short- Lived Reactive Intermediate in the Decomposition of Formate on NiO(111) Surface Observed by Picosecond Temperature Jump. J. Phys. Chem. B 1998, 102(31), 5951-5954.

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10. Xu, C.; Goodman, D. W., Adsorption and Reaction of Formic Acid on the Mo(110) and O/Mo(110) Surfaces. J. Phys. Chem. 1996, 100(5), 1753-1760.

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12. Bulushev, D. A.; Beloshapkin, S.; Ross, J. R. H., Hydrogen from Formic Acid Decomposition over Pd and Au Catalysts. Catal. Today 2010, 154(1–2), 7-12.

13. Singh, S.; Li, S.; Carrasquillo-Flores, R.; Alba-Rubio, A. C.; Dumesic, J. A.; Mavrikakis, M., Formic Acid Decomposition on Au Catalysts: DFT, Microkinetic Modeling, and Reaction Kinetics Experiments. AIChE J. 2014, 60(4), 1303-1319.

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14. Wortman, R.; Gomer, R.; Lundy, R., Adsorption and Diffusion of Hydrogen on Nickel. J. Chem. Phys. 1957, 27(5), 1099-1107.

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16. Sun, X.; Hwang, J.-Y.; Shi, S., Hydrogen Storage in Mesoporous Metal Oxides with Catalyst and External Electric Field. J. Phys. Chem. C 2010, 114(15), 7178-7184.

17. Zhou, J.; Wang, Q.; Sun, Q.; Jena, P.; Chen, X. S., Electric Field Enhanced Hydrogen Storage on Polarizable Materials Substrates. P. Natl. Acad. Sci. 2010, 107(7), 2801-2806.

18. Block, J. and Moentack, P.L., Assoziationsreaktionen in elektrischen Feldern, Untersuchungen mit der Feldimpuls-Desorption im Feldionen-Massenspektrometer. Z. Naturforschg. 1967, 22a, 711-717.

19. Beckey, H. D. Field Ionization Mass Spectrometry. Friedr. Vieweg & Sohn GmbH: Braunschweig, German Democratic Republic, 1971.

Chapter 4

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2. Bergmann, K.; Eigen, M.; De Maeyer, L., Dielektrische Absorption als Folge Chemischer Relaxation. Berich. Bunsen. Phys. Chem. 1963, 67(8), 819-826.

3. Che, F.; Gray, J. T.; Ha, S.; McEwen, J.-S., Catalytic Water Dehydrogenation and Formation on Nickel: Dual Path Mechanism in High Electric Fields. J. Catal. 2015, 332, 187-200.

4. Che, F.; Gray, J. T.; Ha, S.; McEwen, J.-S., Reducing Reaction Temperature, Steam Requirements, and Coke Formation During Methane Steam Reforming Using Electric Fields: A Microkinetic Modeling and Experimental Study. ACS Catalysis 2017, 7(10), 6957-6968.

5. Che, F.; Gray, J. T.; Ha, S.; McEwen, J.-S., Improving Ni Catalysts Using Electric Fields: A DFT and Experimental Study of the Methane Steam Reforming Reaction. ACS Catalysis 2017, 7(1), 551-562.

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6. Jefimenko, O., Demonstration of the Electric Fields of Current-Carrying Conductors. Am. J. Phys. 1962, 30 (1), 19-21.

7. Jacobs, R.; de Salazar, A.; Nassar, A., New Experimental Method of Visualizing the Electric Field due to Surface Charges on Circuit Elements. Am. J. Phys. 2010, 78, 1432- 1433.

8. Seiler, H., Secondary Electron Emission in the Scanning Electron Microscope. J. Appl. Phys. 1983, 54(11), R1-R18.

Chapter 5

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2. Che, F.; Gray, J. T.; Ha, S.; McEwen, J.-S., Reducing Reaction Temperature, Steam Requirements, and Coke Formation During Methane Steam Reforming Using Electric Fields: A Microkinetic Modeling and Experimental Study. ACS Catal. 2017, 7(10), 6957- 6968.

3. Che, F.; Zhang, R.; Hensley, A. J.; Ha, S.; McEwen, J.-S., Density Functional Theory Studies of Methyl Dissociation on a Ni(111) Surface in the Presence of an External Electric Field. Phys. Chem. Chem. Phys. 2014, 16(6), 2399-2410.

4. Gray, J. T.; Che, F.; McEwen, J. S.; Ha, S., Field-Assisted Suppression of Coke in the Methane Steam Reforming Reaction. Applied Catalysis B: Environmental 2019.

5. Bricknell, R. H.; Woodford, D. A., The Embrittlement of Nickel Following High Temperature Air Exposure. Metall.Trans. A 1981, 12(3), 425-433.

6. De Falco, M.; Piemonte, V.; Di Paola, L.; Basile, A., Methane Membrane Steam Reforming: Heat Duty Assessment. Int. J. Hydrogen Energ. 2014, 39(9), 4761-4770.

Chapter 6

1. Neagu, D.; Oh, T.-S.; Miller, D. N.; Ménard, H.; Bukhari, S. M.; Gamble, S. R.; Gorte, R. J.; Vohs, J. M.; Irvine, J. T. S., Nano-socketed Nickel Particles with Enhanced Coking Resistance Grown in situ by Redox Exsolution. Nature Comm. 2015, 6, 8120.

2. Bruno, T. J.; Huber, M. L.; Laesecke, A.; Lemmon, E. W.; Perkins, R. A., Thermochemical and Thermophysical Properties of JP-10. National Institute of Standards and Technology, Fuels Branch, Turbine Engine Division; Propulsion Directorate, AFRL; Wright Patterson Air Force Base, Ohio 45433, 2006.

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3. Han, K.-J.; Hwang, I.-C.; Park, S.-J.; Choi, M.-J.; Lee, S.-B.; Han, J.-S., Vapor–liquid Equilibrium, Densities and Viscosities for the Binary System exo- and endo- tetrahydrodicyclopentadiene and Pure Component Vapor Pressures. Fluid Phase Equilibr. 2006, 249(1), 187-191.

4. Cocke, D. L.; Chuah, G. K.; Kruse, N.; Block, J. H., Copper Oxidation and Surface Copper Oxide Stability Investigated by Pulsed Field Desorption Mass Spectrometry. Appl. Surf. Sci. 1995, 84(2), 153-161.

5. Tsong, T. T., Effects of an Electric Field in Atomic Manipulations. Phys. Rev. B 1991, 44(24), 13703-13710.

Chapter 7

1. Nagai, K., Anisotropies of Polarizability of n‐Alkanes. J. Chem. Phys. 1967, 47(11), 4690- 4696.

2. Miller, K. J., Additivity Methods in Molecular Polarizability. J. Am. Chem. Soc. 1990, 112(23), 8533-8542.

3. Wilson, L. O., Changes in Sulfur Content and Isotopic Ratios of Sulfur during Petroleum Maturation; Study of Big Horn Basin Paleozoic Oils. AAPG Bull. 1974, 58(11), 2294-2318.

4. Han, Y.; Zhang, Y.; Xu, C.; Hsu, C. S., Molecular Characterization of Sulfur-Containing Compounds in Petroleum. Fuel 2018, 221, 144-158.

5. Fan, H.; Zhang, Y.; Lin, Y., The Catalytic Effects of Minerals on Aquathermolysis of Heavy Oils. Fuel 2004, 83(14), 2035-2039.

6. Bauschlicher, C. W., On the Similarity of the Bonding in NiS and NiO. Chem. Phys. 1985, 93(3), 399-404.

7. Iulianelli, A.; Ribeirinha, P.; Mendes, A.; Basile, A., Methanol Steam Reforming for Hydrogen Generation via Conventional and Membrane Reactors: A Review. Renew. Sust. Energ. Rev. 2014, 29, 355-368.

8. Lan, R.; Irvine, J. T. S.; Tao, S., Ammonia and Related Chemicals as Potential Indirect Hydrogen Storage Materials. Int. J. Hydrogen Energ. 2012, 37(2), 1482-1494.

9. Haryanto, A.; Fernando, S.; Murali, N.; Adhikari, S., Current Status of Hydrogen Production Techniques by Steam Reforming of Ethanol: A Review. Energ. Fuel. 2005, 19(5), 2098-2106.

10. Sarkar, N.; Ghosh, S. K.; Bannerjee, S.; Aikat, K., Bioethanol Production from Agricultural Wastes: An Overview. Renew. Energ. 2012, 37(1), 19-27.

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11. Sun, Y.; Cheng, J., Hydrolysis of Lignocellulosic Materials for Ethanol Production: A Review. Bioresource Technol. 2002, 83(1), 1-11. 12. Rathmann, R.; Szklo, A.; Schaeffer, R., Land Use Competition for Production of Food and Liquid Biofuels: An Analysis of the Arguments in the Current Debate. Renew. Energ. 2010, 35(1), 14-22.

13. Caspeta, L.; Buijs, N. A. A.; Nielsen, J., The Role of Biofuels in the Future Energy Supply. Energ. Environ. Sci. 2013, 6(4), 1077-1082.

14. Thompson, P. B., The Agricultural Ethics of Biofuels: The Food vs. Fuel Debate Agriculture 2012, 2(4), 339-358.

15. Alves, H. J.; Bley Junior, C.; Niklevicz, R. R.; Frigo, E. P.; Frigo, M. S.; Coimbra-Araújo, C. H., Overview of Hydrogen Production Technologies from Biogas and the Applications in Fuel Cells. Int. J. Hydrogen Energ. 2013, 38(13), 5215-5225.

16. Braga, L. B.; Silveira, J. L.; da Silva, M. E.; Tuna, C. E.; Machin, E. B.; Pedroso, D. T., Hydrogen Production by Biogas Steam Reforming: A Technical, Economic and Ecological Analysis. Renew. Sust. Energ. Rev. 2013, 28, 166-173.

17. Singh, S.; Li, S.; Carrasquillo-Flores, R.; Alba-Rubio, A. C.; Dumesic, J. A.; Mavrikakis, M., Formic Acid Decomposition on Au Catalysts: DFT, Microkinetic Modeling, and Reaction Kinetics Experiments. AIChE J. 2014, 60(4), 1303-1319.

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APPENDIX

APPENDIX A: THE BERGMANN EQUATION

Many papers on the effects of an electric field on chemical reactions cite what will henceforth be referred to as “the Bergmann equation” as evidence of the thermodynamic-altering effects of electric fields. Frequently, however, this relationship is incorrectly described or confusingly defined, leading to mistakes propagating through the literature. This mistake has been difficult to correct because the Bergmann equation is never explicitly (i.e. step-by-step) derived and certain terms were never explicitly mathematically defined by the original authors. The first example of such definitions for these terms appear in the English literature in a review 13 years after the original paper by Bergmann et al. was published. Although several authors have used the

Bergmann equation to describe physical phenomena and compare to experiment, it is doubtful that they did so using the Bergmann equation as a starting point. Indeed, we only noted the error ourselves while trying to use the Bergmann equation as a starting point for computations and discovered dimensional inconsistencies. This Appendix provides a detailed description of the literature regarding the Bergmann equation (especially where publications in German are concerned) and attempts to clarify for the reader what may have been meant by the original authors.

It is also shown that a potential error in transcribing the equation may have propagated inadvertently through the English literature.* Finally a derivation of the original Bergmann equation from first principles is provided as well as a brief note on the rigorous application of statistical mechanics.

* Note that the papers cited herein have likely used more fundamental physics to perform their computations rather than using the Bergmann equation as a starting point (as already mentioned). Hence, we see no reason their results should be inaccurate (indeed, they contain no obviously erroneous results). The aim of this Appendix is to highlight and clear up confusion in definitions specifically related to the Bergmann equation and help future readers avoid mistakes resulting from this confusion.

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The effects of an electric field on the thermodynamics of chemical reactions were first described by Bergmann, Eigen, and De Maeyer in their 1963 paper Dielektrische Absorption als

Folge chemischer Relaxation, or Dielectric Absorption as a Result of Chemical Relaxation [1].

Herein, they establish a van’t Hoff-style relationship between the equilibrium constant (K) of a reaction and an applied electric field (|F|):*

∂ ln K ∆M = A1 ∂ |F| RT where T is the reaction temperature and R is the universal gas constant. It should be noted that the

∆M term is never mathematically defined—an oversight which may have been the source of most of the confusion in the later literature. When Bergmann et al. defined ∆M, they wrote:

“The quantity ∆푀 is—like reaction enthalpy and reaction volume—a differential partial molar quantity for reactants and reaction products, in this case the state variable conjugated to [퐹], the electric moment 푀.” (translated from German, page 820)

Here, Bergmann et al. are comparing the electrical moment, M, to other state variables to highlight the electric field’s thermodynamic similarity to quantities like temperature and pressure.

The differential quantity, ∆M, is clearly meant to refer to a difference between products and reactants in the same way as reaction enthalpy is defined as “products minus reactants.” No direct citation is provided for this statement, but a 1936 paper by Lars Onsager is cited later in the paper which discusses the electric moment term in more depth [2]. The definition of M that Onsager provides on page 1488 of his work is:**

* While Bergmann et al. used the symbol E to represent the electric field, the symbol F is used throughout the rest of this dissertation to (i) align with physics nomenclature (most common among theoreticians), and (ii) distinguish it from energy which is often given the symbol E. Notes will be provided where symbols have been changed from their original paper for clarity. ** Onsager uses m rather than M. The unit vector term, u, has also been omitted for simplicity.

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M = μ + αF A2 where μ and α are the dipole moment and polarizability of the molecule in question. The choice of nomenclature by Bergmann et al. (M) coincides with their use of the term “electric moment” and points to the intended use of Onsager’s definition of M (Equation A2).

Aside from the obtuse definition of ∆M used by Bergmann et al. (the phrase “like reaction enthalpy” has probably created much confusion), another unfortunate definition used later in the paper may also have contributed to misunderstandings. Perhaps in an attempt to be as rigorous as possible, reaction properties are defined using the extent of reaction:

“The symbol ∆ always denotes the operator (휕⁄휕휉) with the intensive variables (푇, 푃, [퐹]) fixed.” (translated from German, page 823)* Consistent with the definitions used for other state variables, this boils down to finding the difference between the total electrical moment of the products and the total electrical moment of the reactants modified by appropriate stoichiometric coefficients. This same definition is reiterated in Methods in Enzymology (Chapter 4: Electric Field Methods, written in English) by De Maeyer in 1969, 6 years after the original Bergmann publication:

∂M ∆M = ( ) A3 ∂ξ T,P,F where

“the variable 휉 is the extent of reaction, expressed by the number of mole equivalents transformed” (page 81) [3]

Like Bergmann et al., De Maeyer never explicitly writes out a definition of M, but does refer to it as “the macroscopic electric moment of the system,” so there is a general concordance

* Note: original symbol used for electric field was E rather than F.

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between the papers. The same definition is reiterated by Hellemans and De Maeyer in a 1975 paper

[4].

The first time a formal definition of M appears in the English literature accompanying a discussion of the Bergmann equation is in a 1976 review of surface reactions in high fields by

Block [5]. Although the Bergmann paper is directly cited, the ∆M term is incorrectly translated as

“an electric momentum” (page 144) and is defined as:

1 ΔM = [Σμ − Σμ ]F + [Σα − Σα ]F2 A4 p r 2 p r

Aside from a minor misinterpretation of “moment” into “momentum,” Block presents generally the correct idea: that the total property of the products must be subtracted from the total property of the reactants (subscript p and r). The definition shown in Equation A4 likely comes from a previous use in a German paper by Block and Moentack which defined the quantity ∆M as:

“…the electrical moment ∆푀…is the difference of the field energies, 퐸퐹 = 휇퐹 + 1⁄2 훼퐹2 of the reaction products and reactants.” (translated from German, page 712) [6] Although Block and Moentack use the correct terminology (“electrical moment”) they immediately redefine it as a “field energy” using a completely different symbol (EF) within the same sentence. The invalidity of this interpretation is obvious when Equations A1 and A4 are compared dimensionally:*

1 1 V C ∙ m2 V2 ≟ ((C ∙ m) ( ) + ( ) ( )) V J 2 A5 ( ) m V m (m) (K) K

* The universal gas constant R in Equation A1 has here been changed to the Boltzmann constant, kB, to avoid molar ν푖 ν푖 terms. Equilibrium constant is dimensionless by definition: K ≡ ∏푖(α푖) ≈ ∏푖(P푖⁄Pstd) where α푖 is chemical activity (a unitless term), ν푖 are stoichiometric coefficients, and P푖 and Pstd are the partial and standard pressures, for chemical species 푖.

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whereupon, after simplification, the left-hand side reduces to (m⁄V) and the right-hand side is unity. Upon similar analysis with Equations A1 and A2 (which simply eliminates a V/m term from the right-hand side of Equation A5), the left- and right-hand terms return consistent units of

(m⁄V). Considering the slightly confusing definitions laid out by Bergmann and De Maeyer using extent of reaction (ξ) shown in Equation A3 and the original usage of the symbol E for the electric field, it is possible that this mistake came about due to confusion related to the integrated versus the differentiated forms of the equation. Thus the definition of the electric moment outlined by

Onsager (Equation A2) may have been inadvertently integrated to yield Equation A4. It is also possible that working with Equation A1, the ∆M term was assumed to be a constant and later substituted with the correctly integrated form. It could also be a simple case of miscommunication: since Block redefines ∆M as EF in the original German usage, it may have been intended to be used only with the integrated form of the Bergmann equation. Because this is the first instance in the English literature of a definition of the electric moment directly accompanied by a discussion of the Bergmann equation, it seems likely that other readers took this at face value rather than investigating further. The mistake would not be noticed by the author or reviewers, either, since no computations were being carried out directly with the equation.

The substitution of the integrated form of ∆M appears again in a 1978 paper on the reactions of sulfur on metal surfaces in high electric fields by Abend, Abitz, and Block [7]:

1 ∆M = Σ∆μF + Σ ∆αF2 + ⋯ A6 2

The description of this expression is accurate, although it further obscures the original:

“… where ∆푀, as a partial molar energy, is determined by the electric moment of a reaction and the field strength.” (page 262)

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It is worth noting that Equations A4 and A6, as written, do indeed represent energy terms

(the units simply to (J)) and that Equation A6 has also been truncated, represented by an ellipsis, omitting hyperpolarizability terms. This is the first time hyperpolarizability terms have been mentioned in any of the high-field chemistry work, and was described in detail in the chemical literature by Buckingham in the Proceedings of the 31st International Meeting of the Societe de

Chimie Physique (page 217), just 44 pages before the Abend, Abitz, and Block paper on sulfur reactions in which this ∆M term appears [8].

The next available reference to the Bergmann equation was written by Kreuzer in Chapter

18 of Surface Science of Catalysis: In Situ Probes and Reaction Kinetics [9]. Here ∆M is again described as “… a partial molar energy related to the change in electric moment in the reaction” and written as:*

1 ∆M = ∆μF + ∆αF2 + ⋯ A7 2

Kreuzer uses this same description again in 1994 and 2004 papers with the same name, but does not explicitly write out a mathematical formulation of ∆M [10, 11].

This apparently integrated form of the electrical moment is actually correctly used to define changes in the electrical energy of molecules in the presence of a field (hence its use in these corrupted versions of ΔM when interpreted as energy):

1 U = U − μF − αF2 + ⋯ A8 0 2

* Kreuzer uses p rather than μ.

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here, U and U0 represent the potential energies in the presence and absence of an electric field, respectively. Hyperpolarizability terms have again been truncated. More details on Equation A8 can be found in work by Sowlati-Hasjin and Matta from 2013 [12]. This same definition was used by Block in 1963 to describe the potential energy of a molecule in an electric field (VF) with respect to its dipole moment (μ) and polarizability (α) [13]:

1 −V = μF + αF2 A9 F 2

Block also defines the equilibrium partial pressure of a molecule in an electric field (PF) as being proportional to the field-free partial pressure (P0) using a Boltzmann relationship:

V − F A10 PF = P0e kT

Equation A1 can be derived directly from these two definitions. Using a generic gas-phase reaction:

a A + b B → c C + d D A11 where a, b, c, and d are stoichiometric coefficients for chemical species A, B, C, and D respectively. The field-dependent and independent equilibrium constants (KF and K0, respectively) can then be defined assuming standard conditions:

c d −a −b P푖 PC PD PA PB K = ∏ ( ) = ( ) ( ) ( ) ( ) A12 Pstd Pstd Pstd Pstd Pstd 푖 where Pstd represents standard pressure. The ratio KF/K0 simplifies to:

K P c P d P −a P −b F = ( F,C) ( F,D) ( F,A) ( F,B) A13 K0 P0,C P0,D P0,A P0,B

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The partial pressure ratios for each species in Equation A13 can then be substituted by the exponential term of Equation A10 and combined to:

KF 1 = exp (− (cVF,C + dVF,D − aVF,A − bVF,B)) A14 K0 kT

The argument of this exponential is a classic “products minus reactants” style description which can be rearranged and defined as “deltas” as described by Bergmann (Equation A3):

−(cVF,C + dVF,d − aVF,A − bVF,B)

1 = (cμ + dμ − aμ − bμ )F + (cα + dα − aα − bα )F2 C D A B 2 C D A B A15 1 = ∆μF + ∆αF2 2

This substituted expression, when rearranged, can then be differentiated with respect to the electric field, F, to determine the dependence on equilibrium constant with respect to F:

∂ ∂ 1 1 1 (ln K ) = ( (∆μF + ∆αF2) + ln K ) = (∆μ + ∆αF) A16 ∂F F ∂F kT 2 0 kT

Thus the right-hand side of the differential form of Equation A16 takes on the form of the electric moment defined by Onsager, but the integrated form uses the electric potential energy defined in Equations A8 and A9.

As an additional related cautionary note, the dipole moment of a molecule (μ) in a large number of molecules in weak electric fields must be adjusted for electric field screening and polarization of the bulk material. All of the available literature on this screening effect focuses on condensed-phase (e.g. ions in liquids, solids, or “electron gases”) so this correction may not apply

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to gas-phases.* However, although the work conducted in this dissertation is completely gas-phase, it could be argued that surface-adsorbed species formed during heterogeneous catalysis behave as a condensed phase and require this same treatment. Formic acid multilayer adsorption certainly occurs at low temperatures, for example, so this additional factor may be needed for low- temperature experiments as was done by Block [6, 14]. In this work, a mean dipole moment (μ̅) for the condensed phase was determined using a correction factor known as the Langevin function

(L):

μF kT μ̅ = μL = μ (coth ( ) − ) A17 kT μF

The Langevin function is a unitless quantity and does not change the dimensional analysis presented earlier. Essentially, this corrects for field screening by randomly oriented dipoles

(introducing an F−1 term into the equations). However, this term is generally omitted in high-field applications such the work presented in this dissertation since Equation A17 reduces to μ in the limit of high fields:

μF kT lim μ̅ = μ lim (coth ( ) − ) = μ A18 F→ ∞ F→ ∞ kT μF

The hyperbolic cotangent approaches unity as its argument grows and the ratio approaches zero. This describes the physical phenomenon of dipoles orienting with the field, shifting the distribution to a less randomly arranged one. Thus, for most high-field applications, the electric moment can be assumed to hold without requiring a screening correction—though this can

* This is difficult to verify in literature, as theoretical physics appears to not make a distinction between phases. Practical literature focuses on liquid phases (especially ions in water) and solids. One brief statement by Smith et al. in 1995 (“…screening effects which would result from atoms from other molecules…will not occur in the gas phase…” (pages 530 and 531) [15] and a preprint arXiv article entitled “Why the Langevin-Debye Theory of Molecular Polarisation Fails in Gas Phase” from 2005 by Mauizio [16] were the only direct sources found to support this idea.

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certainly be added in the interest of completeness. In cases where it may be beneficial to simplify the computation of L, L can be approximated at very low field strengths using a Taylor series expansion about F = 0:

휇퐹 푘푇 푘푇 1 휇퐹 1 휇퐹 3 2 휇퐹 5 푘푇 1 휇퐹 퐿 = coth ( ) − ≈ + − ( ) + ( ) + ⋯ − ≈ A19 푘푇 휇퐹 휇퐹 3 푘푇 45 푘푇 945 푘푇 휇퐹 3 푘푇

It should be noted that this simplification can be used for very low fields where the correct limit of the dipole approaching zero as F approaches zero holds (physically this represents dipole cancellation due to random orientation in weak fields). This approximation can be assumed to hold fairly well for μF⁄kT ≪ 1 [17].

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References

1. Bergmann, K.; Eigen, M.; De Maeyer, L., Dielektrische Absorption als Folge Chemischer Relaxation. Berich. Bunsen. Phys. Chem. 1963, 67(8), 819-826.

2. Onsager, L., Electric Moments of Molecules in Liquids. J. Am. Chem. Soc. 1936, 58(8), 1486-1493.

3. De Maeyer, L. C. M., Electric Field Methods. Method Enzymol. 1969; 16, 80-118.

4. Hellemans, L.; Maeyer, L. D., Absorption and Dispersion of the Field Induced Dielectric Increment in Caprolactam–Cyclohexane Solutions. J. Chem. Phys. 1975, 63(8), 3490- 3498.

5. Block, J. H., Chemical Surface Reactions in the Presence of High Electric Fields. CRC Cr. Rev. Sol. State 1976, 6(2), 133-156.

6. Block, J. and Moentack, P.L., Assoziationsreaktionen in elektrischen Feldern, Untersuchungen mit der Feldimpuls-Desorption im Feldionen-Massenspektrometer. Z. Naturforschg. 1967, 22a, 711-717.

7. Abend, G.; Abitz, R.-G.; Block, J. H., Influences of High Electric Fields on Surface Reactions of Sulfur on Metals, Investigated by Field Desorption. In Nonlinear Behaviour of Molecules, Atoms, and Ions in Electric, Magnetic, or Electromagnetic Fields, Néel, L., Ed. Elsevier Scientific Pub Co.: New York, 1979.

8. Buckingham, A. D., Hyperpolarizability. In Nonlinear Behaviour of Molecules, Atoms, and Ions in Electric, Magnetic, or Electromagnetic Fields, Néel, L., Ed. Elsevier Scientific Pub. Co.: New York, 1979.

9. Kreuzer, H. J., Chemical Reactions in High Electric Fields. In Surface Science of Catalysis, American Chemical Society: 1992; 482, 268-286.

10. Kreuzer, H. J.; Wang, R. L. C., Physics and Chemistry in High Electric Fields. Philos. Mag. B 1994, 69(5), 945-955.

11. Kreuzer, H. J., Physics and Chemistry in High Electric Fields. Suf. Interface Anal. 2004, 36(5), 372-379.

12. Sowlati-Hashjin, S. and Matta C.F., The Chemical Bond in External Electric Fields: Energies, Geometries, and Vibrational Stark Shifts of Diatomic Molecules. J. Chem. Phys. 2013, 139, 144101.

13. Block, J. Über die Feldkondensation und Feldreaktion der Ameisensäure an einigen Metallen. Z. Naturforschg. 1963, 18a, 952-960.

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14. Beckey, H. D. Field Ionization Mass Spectrometry. Friedr. Vieweg & Sohn GmbH: Braunschweig, German Democratic Republic, 1971.

15. Smith, G. D.; Jaffe, R. L.; Yoon, D. Y., Conformations of 1,2-Dimethoxyethane in the Gas and Liquid Phases from Molecular Dynamics Simulations. J. Am. Chem. Soc. 1995, 117(1), 530-531.

16. Maurizio, M. Why the Langevin-Debye Theory of Molecular Polarisation Fails in Gas Phase. arXiv preprint physics/0508167 2005.

17. Poulain, P.; Antoine, R.; Broyer, M.; Dugourd, P. Monte Carlo Simulations of Flexible Molecules in a Static Electric Field: Electric Dipole and Conformation. Chem. Phys. Lett. 2005, 401(1), 1-6.

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APPENDIX B: FORMIC ACID AS A FUEL

Methanol (CH3OH) and formic acid (HCOOH) are both promising fuels for intermittent energy storage and as possible in situ hydrogen sources for proton-exchange membrane (PEM) based hydrogen fuel cells. Both materials are liquids at room temperature and can be synthesized directly from CO2 and H2 [1-9] and both can be converted back into H2 relatively easily [10-17].

Thus, either material could represent the first truly carbon-neutral liquid fuel by converting atmospheric or captured CO2 to fuel using renewable energies as demonstrated in Figure B1.

Figure B1. Using intermittent renewable energy sources to produce H2 (via hydrolysis for example) and synthesize HCOOH allows for storage of excess energy in a safe, environmentally friendly liquid medium that is easy to store and transport. Decomposition to H2 and CO2 in situ (dashed arrows) allows for operation of PEM H2 fuel cells on demand. A similar cycle could be drawn for CH3OH.

Additionally, unlike biofuels, valuable farmland and foodstuffs are not wasted for the production of either CH3OH or HCOOH if synthesized from captured CO2. Proponents of CH3OH as a fuel argue that its energy density is significantly higher than that of HCOOH: 15.0 MJ/kg compared to HCOOH at just 5.21 MJ/kg. For comparison, pure H2 has an energy density of ~120

MJ/kg. These numbers are somewhat deceptive, however, since they do not take into account

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technological limitations. Current H2 storage and transportation technologies, for example, reduce the energy density of H2 fuel to only 5.7% of its theoretical maximum, or just 6.84 MJ/kg [18].

Additionally, the energy density of CH3OH depends strongly on the type of reactions it is used for.

A realistic on-board CH3OH reformer for transportation purposes must necessarily operate under partial oxidation (POX) conditions using ambient air to avoid carrying other liquid oxidizers on board, such as H2O. Operating a CH3OH reformer under POX conditions can reduce H2 production by 41-66% compared to the theoretical maximum (i.e. 6.15 - 9.90 MJ/kg) [19]. In terms of energy density and current technological limitations, then, both CH3OH and HCOOH are attractive options and comparable to H2 fuel. Beyond the energy density issue, however, safety concerns must also be considered when designing fuel systems for transportation applications.

Whether stored as a liquid or a gas, the use of H2 as a fuel comes with significant risks due to its highly explosive nature. Hazards for both CH3OH and HCOOH are much less severe compared to H2 and are, again, comparable to one another. For example, since the well-known toxicity of CH3OH is due to the formation and accumulation of HCOOH during metabolism in the body, both materials pose similar health risks [20, 21]. Both liquids also receive scores of 3 for flammability and 2 for health hazards by the National Fire Protection Association (NFPA), however, the NFPA reactivity rating is a 1 for HCOOH and a 0 for CH3OH. This is because

HCOOH is a weak organic acid (pKa = 3.75). Special considerations must therefore be taken to use compatible materials for commercial HCOOH reactors such as poly(tetrafluoroethylene).

HCOOH does have certain safety advantages over CH3OH, however. For example, the vapor pressure of HCOOH at 20 °C is about 33% that of CH3OH. The flash point is therefore much higher: 49.5 °C for HCOOH and 9.70 °C for CH3OH (gasoline flashes at -45.0 °C). Thus, while a

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CH3OH refueling station would be safer than a traditional gasoline fuel station, fires started from errant sources such as cigarettes or electrical discharges would be unheard of at a HCOOH fueling station. Additionally, since CH3OH fires burn blue and don’t produce soot, they are nearly invisible—a safety concern for firefighters.

As one further point of difference, the freezing points of CH3OH and HCOOH are -98 and

8.3 °C, respectively. Thus, the use of HCOOH is limited only to regions where temperatures do not fall below 8 °C. This can be mitigated somewhat by mixing HCOOH with H2O: a 90%

HCOOH should have a freezing point of -9 °C or -30 °C for an 80% solution (kf,HCOOH = -2.77

°C/m). Since HCOOH is extremely hygroscopic and adding H2O to HCOOH has been shown to improve reactivity and selectivity over many catalysts, this may already be done to improve the fuel or occur naturally over time. Of course, any additional water blended into the fuel represents useless weight that must be carried around, reducing the efficiency of the system. This may be a considerable drawback of using HCOOH as a liquid fuel.

Water is, however, also a necessary ingredient for CH3OH steam reforming, one of the two viable choices for using CH3OH as a H2 source:

CH3OH + H2O → CO2 + 3H2 B1

However, this would require carrying significantly more H2O than the 80-90% HCOOH solution discussed previously. Direct decomposition of CH3OH produces CO, which is detrimental to PEM-based fuel cells and would require either another unit operation to convert or separate the

CO from the fuel stream:

CH3OH → 2H2 + CO B2

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The most likely H2 producing reaction for a commercial CH3OH reformer for transportation purposes is therefore POX in air as mentioned earlier:

CH3OH + ½ O2 → 2H2 + CO2 B3

It has been suggested that the catalytic POX of CH3OH proceeds through a formate intermediate [22-24], a chemical species that is also produced during the catalytic decomposition of HCOOH. Those on both sides of the fuel debate can therefore benefit from a better understanding of the decomposition of HCOOH.

Two possible decomposition pathways are available for HCOOH: dehydration (Equation

B4) and decarboxylation (Equation B5):

HCOOH → H2O + CO B4

HCOOH → H2 + CO2 B5

The decarboxylation reaction of HCOOH is extremely desirable because it, unlike many

H2-producing reactions, can generate CO-free H2 without the use of additional reagents or unit operations. This is beneficial for mobile applications since it limits the controller complexity required for maintaining optimal feed ratios and reduces the total volume of the reformer unit.

To be useful as a liquid H2 precursor in mobile applications, such as for PEM fuel cell- based cars, the decomposition must utilize as little energy as possible to generate H2 gas. Many catalysts capable of facilitating HCOOH decarboxylation at room temperature have been reported in the past several years including Pd/C nanoparticles [25], Ag-Pd core-shell nanoparticles [14], and heterogeneous Ru-phosphine catalysts [15]. There are several difficulties with these catalysts which present barriers to their utility in commercial HCOOH reformers—the most obvious of which is that they are all noble-metal based. Noble metals are undesirable commercial catalysts

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due to their limited availability and high cost. Difficult syntheses (especially of core-shell particles) further add to the high cost barrier of these catalysts. More earth-abundant, low-cost materials are therefore desirable in the search for low-temperature HCOOH reforming catalysts.

Additional tuning of these low-cost catalyst may be achieved using EFAC, though for this to work in a mobile application the applied potential would have to be quite low (e.g. to run on a car battery).

Studying the effects of EFAC on a HCOOH decomposition system over non-ideal (i.e. non-noble metal based) catalysts is then not only an interesting exercise in exploring possible future fuel systems but can also give some valuable fundamental insights into the properties and principles of EFAC.

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1. Moret, S.; Dyson, P. J.; Laurenczy, G., Direct Synthesis of Formic Acid from Carbon Dioxide by Hydrogenation in Acidic Media. Nature Comm. 2014, 5.

2. Rasmussen, P. B.; Kazuta, M.; Chorkendorff, I., Synthesis of Methanol from a Mixture of H2 and CO2 on Cu(100). Surf. Sci. 1994, 318(3), 267-280.

3. Zhuang, H.-d.; Bai, S.-f.; Liu, X.-m.; Yan, Z.-f., Structure and Performance of Cu/ZrO2 Catalyst for the Synthesis of Methanol from CO2 Hydrogenation. J. Fuel Chem. Technol. 2010, 38(4), 462-467.

4. Graciani, J.; Mudiyanselage, K.; Xu, F.; Baber, A. E.; Evans, J.; Senanayake, S. D.; Stacchiola, D. J.; Liu, P.; Hrbek, J.; Sanz, J. F.; Rodriguez, J. A., Highly Active Copper- Ceria and Copper-Ceria-Titania Catalysts for Methanol Synthesis from CO2. Science 2014, 345(6196), 546-550.

5. Liu, X.-M.; Lu, G. Q.; Yan, Z.-F.; Beltramini, J., Recent Advances in Catalysts for Methanol Synthesis via Hydrogenation of CO and CO2. Ind. Eng. Chem. Res. 2003, 42(25), 6518-6530.

6. Motokura, K.; Kashiwame, D.; Miyaji, A.; Baba, T., Copper-Catalyzed Formic Acid Synthesis from CO2 with Hydrosilanes and H2O. Org. Lett. 2012, 14(10), 2642-2645. 7. Leitner, W., Carbon Dioxide as a Raw Material: The Synthesis of Formic Acid and Its Derivatives from CO2. Angew. Chem. Int. Edit. 1995, 34(20), 2207-2221.

8. Yoshio, I.; Hitoshi, I.; Yoshiyuki, S.; Harukichi, H., Catalytic Fixation of Carbon Dioxide to Formic Acid by Transition-Metal Complexes under Mild Conditions. Chem. Lett. 1976, 5(8), 863-864.

9. Schaub, T.; Paciello, R. A., A Process for the Synthesis of Formic Acid by CO2 Hydrogenation: Thermodynamic Aspects and the Role of CO. Angew. Chem. Int. Edit. 2011, 50(32), 7278-7282.

10. Edwards, J.; Nicolaidis, J.; Cutlip, M. B.; Bennett, C. O., Methanol Partial Oxidation at Low Temperature. J. Catal. 1977, 50(1), 24-34.

11. Cubeiro, M. L.; Fierro, J. L. G., Partial Oxidation of Methanol over Supported Palladium Catalysts. App. Cat. A 1998, 168(2), 307-322.

12. Cubeiro, M. L.; Fierro, J. L. G., Selective Production of Hydrogen by Partial Oxidation of Methanol over ZnO-Supported Palladium Catalysts. J. Catal. 1998, 179(1), 150-162.

13. Deo, G.; Wachs, I. E., Reactivity of Supported Vanadium Oxide Catalysts: The Partial Oxidation of Methanol. J. Catal. 1994, 146(2), 323-334.

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14. Tedsree, K.; Li, T.; Jones, S.; Wong, C.; Chan, A.; Yu, K. M. K.; Bagot, P. A. J.; Marquis, E. A.; Smith, G. D. W.; Tsang, S. C. E., Hydrogen Production from Formic Acid Decomposition at Room Temperature using a Ag-Pd Core-Shell Nanocatalyst. Nature Nano. 2011, 6, 302-307.

15. Loges, B.; Boddien, A.; Junge, H.; Beller, M., Controlled Generation of Hydrogen from Formic Acid Amine Adducts at Room Temperature and Application in H2/O2 Fuel Cells. Angew. Chem. Int. Edit. 2008, 47(21), 3962-3965.

16. Zhou, X.; Huang, Y.; Xing, W.; Liu, C.; Liao, J.; Lu, T., High-quality Hydrogen from the Catalyzed Decomposition of Formic Acid by Pd-Au/C and Pd-Ag/C. Chem. Comm. 2008, 3540-3542.

17. Ojeda, M.; Iglesia, E., Formic Acid Dehydrogenation on Au-Based Catalysts at Near- Ambient Temperatures. Angew. Chem. 2009, 121(26), 4894-4897.

18. Eppinger, J.; Huang, K.-W., Formic Acid as a Hydrogen Energy Carrier. ACS Energ. Lett. 2017, 2(1), 188-195.

19. Lindström, B.; Pettersson, L. J., Hydrogen Generation by Steam Reforming of Methanol over Copper-based Catalysts for Fuel Cell Applications. Int. J. Hydrogen Energ. 2001, 26(9), 923-933. 20. Liesivuori, J.; Savolainen; Heikki, Methanol and Formic Acid Toxicity: Biochemical Mechanisms. Pharmacol. Toxicol. 1991, 69(3), 157-163.

21. Tephly, T. R., The Toxicity of Methanol. Life Sciences 1991, 48(11), 1031-1041.

22. Cao, C.; Hohn, K. L., Study of Reaction Intermediates of Methanol Decomposition and Catalytic Partial Oxidation on Pt/Al2O3. App. Cat. A 2009, 354(1), 26-32.

23. Fu, S. S.; Somorjai, G. A., Roles of Chemisorbed Oxygen and Zinc Oxide Islands on Copper (110) Surfaces for Methanol Decomposition. J. Phys. Chem. 1992, 96(11), 4542- 4549.

24. Peppley, B. A.; Amphlett, J. C.; Kearns, L. M.; Mann, R. F., Methanol–Steam Reforming on Cu/ZnO/Al2O3 Catalysts. Part 2. A Comprehensive Kinetic Model. App. Cat. A 1999, 179(1), 31-49.

25. Wang, Z.-L.; Yan, J.-M.; Wang, H.-L.; Ping, Y.; Jiang, Q., Pd/C Synthesized with Citric Acid: An Efficient Catalyst for Hydrogen Generation from Formic Acid/Sodium Formate. Sci. Rep. 2012, 2, 598.

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APPENDIX C: HYDROCARBON REFORMING

The steam reforming of hydrocarbons is a major player in the production of hydrogen:

CxH2x+2 + xy H2O ⟶ (x(y+1) + 1) H2 + x COy C1

Around 95% of the hydrogen used in the United States of America [1] is produced by methane steam reforming (MSR), and methane is the primary fuel used in 75% of steam reforming units worldwide [2]. The process consists of both CO and CO2 producing reactions as well as the water-gas shift reaction [3]:

CH4 + y H2O ⟶ (y + 2) H2 + COy C2

CO + H2O ⇌ CO2 + H2 C3

The hydrogen thus produced is used in a wide range of critical applications including fertilizer production (Haber-Bosche), petrochemical processing, and scientific research. More recently, gas-to-liquid (GTL) technology has made use of the products of MSR. GTL facilities use the syngas (CO and H2 mixture) produced by MSR plants to create long-chain hydrocarbons through the Fischer-Tropsche process [4, 5]. The motivation behind MSR research should be clear—improvements to this process have a far-reaching and broad impact.

Industrial MSR processes are generally carried out at elevated temperatures above 800 °C, pressures of 10 bar, and using oxygen-to-carbon ratios of 2-6 over nickel catalysts [6]. These factors combined make MSR a very energy-intensive process to run. Such high quantities of water are used for two primary reasons: (i) to prevent coking of the catalyst and (ii) to ensure maximum conversion of methane into H2 and CO2. Thus, much research has been devoted toward improving the coke resistance and reactivity of Ni catalysts: from classical approaches such as doping [7] to the more esoteric including plasma reforming [8-10].

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Longer chain hydrocarbon reforming, though not as industrially relevant as MSR, has some potential commercial applications. Although hydrogen fuel cells are well-established and characterized technologies, they have not seen widespread commercial use. This is for a number of reasons including lack of infrastructure and safety concerns around hydrogen storage [11].

Moreover, as stated previously, most H2 is produced by MSR requiring massive amounts of energy and creating CO2 in the process. Thus, the general push for H2 technology from an environmental standpoint has mostly fizzled out. Nevertheless, many researchers have proposed the use of in situ reformers to complement H2 fuel cells [12]. Such devices would operate on liquid hydrocarbons

(like gasoline [13] or jet fuel [14]) using existing infrastructure. The fuel would be reformed in the vehicle or fueling station into the H2 fuel used to operate a proton exchange or solid oxide fuel cell

[15, 16]. This idea has seen significant interest in recent decades due to the high energy efficiency of fuel cells compared to combustion engines (which lose a lot of energy to waste heat production)

[17].

Many researchers have tackled the problem of fuel cell pre-reforming technology from a number of different angles. Although EFAC-induced reforming has not yet been attempted

(preliminary data for this is provided in Chapter 6), at least one group has attempted integrated plasma and fuel cell systems for this purpose [18].

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References

1. Office of Energy Efficiency & Renewable Energy. Hydrogen Production: Natural Gas Reforming. energy.gov/eere/fuelcells/hydrogen-production-natural-gas-reforming (accessed September 2019).

2. Olivieri, A.; Vegliò, F., Process Simulation of Natural Gas Steam Reforming: Fuel Distribution Optimisation in the Furnace. Fuel Process. Technol. 2008, 89(6), 622-632.

3. Latham, D. A.; McAuley, K. B.; Peppley, B. A.; Raybold, T. M., Mathematical Modeling of an Industrial Steam-Methane Reformer for On-line Deployment. Fuel Process. Technol. 2011, 92(8), 1574-1586.

4. Bao, B.; El-Halwagi, M. M.; Elbashir, N. O., Simulation, Integration, and Economic Analysis of Gas-to-Liquid Processes. Fuel Process. Technol. 2010, 91(7), 703-713.

5. Wood, D. A.; Nwaoha, C.; Towler, B. F., Gas-to-Liquids (GTL): A Review of an Industry Offering Several Routes for Monetizing Natural Gas. J. Nat. Gas Sci. Eng. 2012, 9, 196- 208.

6. Bharadwaj, S. S.; Schmidt, L. D., Catalytic Partial Oxidation of Natural Gas to Syngas. Fuel Process. Technol. 1995, 42(2), 109-127.

7. Angeli, S. D.; Turchetti, L.; Monteleone, G.; Lemonidou, A. A., Catalyst Development for Steam Reforming of Methane and Model Biogas at Low Temperature. App. Cat. B 2016, 181, 34-46.

8. Kado, S.; Urasaki, K.; Sekine, Y.; Fujimoto, K., Low Temperature Reforming of Methane to Synthesis Gas with Direct Current Pulse Discharge Method. Chem. Comm. 2001, (5), 415-416.

9. Bromberg, L.; Cohn, D. R.; Rabinovich, A.; Alexeev, N., Plasma Catalytic Reforming of Methane. Int. J. Hydrogen Energ. 1999, 24(12), 1131-1137.

10. Cormier, J. M.; Rusu, I., Syngas Production via Methane Steam Reforming with Oxygen: Plasma Reactors versus Chemical Reactors. J. Phys. D 2001, 34(18), 2798-2803.

11. Ross, D. K., Hydrogen storage: The Major Technological Barrier to the Development of Hydrogen Fuel Cell Cars. Vacuum 2006, 80(10), 1084-1089.

12. Choudhury, A.; Chandra, H.; Arora, A., Application of Solid Oxide Fuel Cell Technology for Power Generation—A Review. Renew. Sus. Energ. Rev. 2013, 20, 430-442.

13. Ming, Q.; Healey, T.; Allen, L.; Irving, P., Steam Reforming of Hydrocarbon Fuels. Catal. Today 2002, 77(1), 51-64.

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14. Zheng, J.; Strohm, J. J.; Song, C., Steam Reforming of Liquid Hydrocarbon Fuels for Micro-fuel Cells. Pre-reforming of Model Jet Fuels over Supported Metal Catalysts. Fuel Process. Technol. 2008, 89(4), 440-448.

15. Zhang, X.; Chan, S. H.; Li, G.; Ho, H. K.; Li, J.; Feng, Z., A Review of Integration Strategies for Solid Oxide Fuel Cells. J. Power Source. 2010, 195(3), 685-702.

16. Joensen, F.; Rostrup-Nielsen, J. R., Conversion of Hydrocarbons and Alcohols for Fuel Cells. J. Power Source. 2002, 105(2), 195-201.

17. Shekhawat, D.; Berry, D. A.; Gardner, T. H.; Spivey, J. J., Catalytic Reforming of Liquid Hydrocarbon Fuels for Fuel Cell Applications. In Catalysis, Spivey, J. J.; Dooley, K. M., Eds. The Royal Society of Chemistry: 2006; 19, 184-254.

18. Galeno, G.; Minutillo, M.; Perna, A., From Waste to Electricity through Integrated Plasma Gasification/Fuel Cell (IPGFC) System. Int. J. Hydrogen Energ. 2011, 36(2), 1692-1701.

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APPENDIX D: CCR PHYSICS DERIVATIONS

The capacitance (C) of a coaxial capacitor is readily derived from its geometry and can be found in any undergraduate physics textbook:

2πLε κ C = 0 D1 ln(c⁄a) where L is the length of the capacitor, ε0 is the permittivity of free space, κ is the relative permittivity of a dielectric between the electrodes, c is the radius of the outer electrode, and a is the radius of the inner electrode. The CCR designs discussed in Chapter 6 are somewhat more complex, however, involving two coaxial dielectric materials (the reactive atmosphere and a quartz or ceramic barrier, assuming the catalyst layer is a conductive surface constituting one of the electrodes). This geometry is shown in Figure D1a.

Figure D1. (a) Cross-sectional view of the CCR design used in Chapter 6 and (b) the equivalent circuit needed for mathematical analysis of this capacitor.

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For a situation like this, the capacitor can be broken into an equivalent circuit for analysis. Since field lines pass through the dielectric materials in series, the system can be analyzed as an equivalent circuit containing two single-dielectric capacitors in series as shown in Figure D1b. The total capacitance of this system is:

−1 −1 −1 Ctotal = (C1 + C2 ) D2

Combining Equations D1 and D2 yields:

2πLε0κ1κ2 Ctotal = D3 κ2ln (b⁄a) + κ1ln (c⁄b)

The electric field within the capacitor is readily evaluated from Gauss’ Law by integrating over a cylindrical Gaussian surface as shown in Figure D2:

Q = ∮ F⃑ ∙ dA⃑⃑ = F ∫ dA = 2πrLF D4 κε0

Here Q is the charge contained on the inner electrode and A and r are the area and radius of the

Gaussian surface.

Figure D2. The Gaussian surface used to evaluate Equation D4.

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From the definition of capacitance:

Q C ≡ D5 V the electric field within each portion of the dielectric can be determined using Equations D3 and

D4:

κ2V F1 = r(κ2 ln(b⁄a) + κ1 ln(c⁄b)) D6 κ1V F2 = r(κ2 ln(b⁄a) + κ1 ln(c⁄b))

Any CCR construction involving two distinct dielectric regions can be evaluated using Equations

D6. Before doing so, however, the system must be carefully defined. For example, a reaction occurring at the inner electrode will require evaluation of r = a + ∆r and a reaction occurring at the outer electrode will require evaluation of r = c − ∆r where ∆r is a small distance (e.g. 2.0 Å) representing the bonding distance. Furthermore, dielectric 1 will be the reactive atmosphere

(mostly Ar) and dielectric 2 will be quartz in a CCRcore configuration while the reverse is true in a

CCRshell configuration (dielectric 1 is ceramic and dielectric 2 is gas).

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