Study of Redox Reactions for Solar Thermochemical Cycles

STUDY OF REDOX REACTIONS FOR SOLAR THERMOCHEMICAL CYCLES

IBRAHEAM ABDULRAHMAN AL-SHANKITI

B.S., University of Tulsa, 2007

M.S., University of Colorado, 2014

A thesis submitted to the

Faculty of the Graduate School of the

University of Colorado in partial fulfillment

of the requirement for the degree of

Doctor of Philosophy

Department of Chemical and Biological Engineering

2018

This thesis entitled:

Study of Redox Reactions for Solar Thermochemical Cycles

written by Ibraheam Abdulrahman Al-Shankiti has been approved for the Department of Chemical and Biological Engineering

______

Alan W. Weimer, Committee Chair

______

Hans H. Funke, Committee Member

Date ______

The final copy of this thesis has been examined by the signatories, and we

find that both the content and the form meet acceptable presentation standards

of scholarly work in the above mentioned discipline.

Al-Shankiti, Ibraheam Abdulrahman (PhD, Chemical and Biological Engineering)

Study of redox reactions for solar thermochemical energy storage and H2O splitting

Thesis directed by Professor Alan W. Weimer

Solar thermal splitting of water or carbon dioxide is a promising technology for producing hydrogen and/or carbon monoxide. In a two-step cycle, a metal oxide is thermally reduced with concentrated solar radiation to release oxygen. The reduced metal oxide is then re- oxidized with steam or carbon dioxide to produce hydrogen or carbon monoxide. The two-step redox cycle can be operated either as a temperature swing where there is a temperature difference between the reduction and oxidation steps or isothermally. This work discusses various aspects of operating the redox cycle isothermally including redox cycle thermodynamics and overall system efficiency and describes solar reactor concepts based on isothermal operation.

This work reports the reduction kinetic study of the hercynite cycle (FeAl2O4) for high temperature solar thermochemical water splitting. The reaction kinetics has been evaluated using dynamic thermogravimetric and XRD analyses. Kinetic modeling results indicate that as- prepared hercynite materials undergoes reduction via two different reaction mechanisms. The reaction first proceeds by a nucleation and growth reaction mechanism, followed by a third-order kinetic model. XRD analyses show the occurrence of superstoichiometric oxygen in the spinel structure of FeAl2O4+δ in the second reaction mechanism, which indicates the formation of cationic vacancies. TGA and XRD analyses show that hercynite materials operates via a cation- vacancy mechanism when the materials are thermally reduced and oxidized with steam.

High-temperature thermochemical energy storage shows promise in aiding concentrating solar power plants in meeting variable, grid-scale electricity demand. In this work, manganese

iii oxide-based mixed metal oxide particles have been designed and tested for high temperature solar thermochemical energy storage. We evaluate the effects of Al2O3, Fe2O3, and ZrO2 in

Mn2O3-based spray-dried particles in a TGA between 650°C and 1,200°C over six consecutive redox cycles. Results are compared with thermodynamic predictions from 400–1,400°C under oxidizing and reducing atmospheres. A mixture of 2:1 Fe2O3:Mn2O3 formed iron manganese oxide spinel (MnFe2O4) on calcination, and demonstrated the highest thermochemical activity.

Conversely, zirconia was an inert support that does not react with manganese oxide. The oxidation reaction kinetics of MnFe2O4 has been evaluated using solid-state kinetics theory and

XRD analysis. A kinetics study indicates that the reaction proceeds by two different reaction mechanisms. The reaction first proceeds by a diffusion-controlled reaction mechanism with no phase change, followed by a nucleation-growth reaction mechanism.

This thesis is dedicated to my beloved family

ACKNOWLEDGMENTS

This work would not have been possible without the help and support of my advisor,

Professor Alan Weimer. He has been a steadfast guide for my journey through my graduate studies. I am also grateful to Team Weimer for their help and support. Many members have contributed to this work. Brian Ehrhart has worked very closely with me and has always been helpful. I take pride in being part of this amazing research group. Research would not be possible without financial support. I would like to acknowledge the financial support toward the research from U.S. DOE Office of Energy Efficiency and Renewable Energy (EERE), Fuel Cell

Technologies Office under Award Number DE-EE0006671. The Saudi Basic Industries

Corporation (SABIC) also has financially supported me to complete my graduate studies.

Hicham Idriss, corporate researcher, offered invaluable support from the beginning of my graduate studies. Thank you Hicham.

Nobody has been more important to me in the pursuit of this project than the members of my family. I would like to thank my parents Abdulrahman and Maryam. They have taught me to learn and be curios. Thank you very much. My siblings have been very supportive. Finally, I want to thank my wonderful wife Khawla who have been so helpful, patient, and kind even when

I have been consumed with this work. There are not enough words to describe her support for me. Thank you and I love you.

CONTENTS

1. INTRODUCTION ...... 1 1.1. Motivation ...... 1

1.2. Solar Thermochemical Water Splitting ...... 1

1.3. Two-Step STWS Active Materials ...... 3

1.3.1. Thermodynamics of STWS Materials ...... 4 1.3.2. Current STWS Materials...... 5 1.4. Project Objectives ...... 15

1.5. References ...... 16

2. ISOTHERMAL REDOX FOR H2O AND CO2 SPLITTING – A REVIEW AND PERSPECTIVE...... 24 2.1. Abstract ...... 24

2.2. Introduction ...... 24

2.3. Chemical thermodynamics ...... 25

2.4. Isothermal vs. non-isothermal ...... 29

2.5. Solar to H2/CO thermodynamic process efficiency model ...... 32

2.5.1. Materials and kinetics effect ...... 34 2.5.2. Reduction reaction processing ...... 35 2.5.3. Heat exchanger effectiveness ...... 38 2.6. Isothermal reactor designs ...... 42

2.6.1. Monolithic-receiver reactors ...... 42 2.7. Summary and path forward ...... 45

2.8. References ...... 46

vii

3. UNDERSTANDING REDUCTION KINETICS OF HERCYNTE MATERIALS FOR SOLAR THERMOCHEMICAL H2O SPLITTING ...... 49 3.1. Abstract ...... 49

3.2. Introduction ...... 49

3.3. Experimental methods ...... 51

3.3.1. Materials preparation ...... 51 3.3.2. Kinetic studies ...... 51 3.3.3. Materials characterization ...... 53 3.4. Results and discussions ...... 54

3.4.1. Experimental TGA results ...... 54 3.4.2. Kinetic modeling ...... 55

3.4.3. Reduction reaction mechanism with H2O splitting ...... 63 3.5. Conclusions ...... 65

3.6. References ...... 65

4. DESIGN OF MANGANESE OXIDE-BASED PARTICLES FOR HIGH-TEMPERATURE THERMOCHEMICAL ENERGY STORAGE ...... 68 4.1. Abstract ...... 68

4.2. Introduction ...... 68

4.3. Methods ...... 72

4.3.1. Particle formation...... 72 4.3.2. Thermodynamic predictions ...... 74 4.3.3. Particle characterization ...... 75 4.3.4. Thermogravimetric analysis...... 75 4.3.5. Oxidation kinetic studies...... 76 4.4. Results and discussion ...... 78

4.4.1. Characterization of spray-dried particles ...... 78

viii

4.4.2. Thermodynamic predictions for candidate materials ...... 81 4.4.3. Thermogravimetric analysis...... 84 4.4.4. Fe67 Oxidation Kinetics ...... 88 4.5. Conclusions ...... 96

4.6. References ...... 97

5. CONCLUSIONS AND RECOMMENDATIONS FOR FUTURE WORK ...... 101 5.1. Summary and conclusions ...... 101

5.1.1. The chemistry and reduction kinetics of the hercynite cycle ...... 101 5.1.2. Iron manganese oxide for solar thermochemical energy storage ...... 102 5.2. Recommendations for Future Work ...... 103

BIBLIOGRAPHY ...... 105

TABLES

Table 2.1: A summary of selected efficiency calculations for solar thermochemical H2O splitting ...... 41 Table 3.1 Solid-state reaction models in differential from...... 52 Table 3.2. Kinetic parameters calculated for the best individual fitting of the experimental at β = 10.0°C/min...... 58 Table 3.3. Kinetic parameters calculated for the best individual fitting of the experimental data for two different regions...... 59 Table 4.1 Overview of composition and sample ID for candidate materials...... 73 Table 4.2. Parameters used in the thermodynamic equilibrium calculations of manganese oxide- based mixed metal oxides...... 74 Table 4.3. Solid-state reaction models in differential from...... 77 Table 4.4. BET surface area (before and after calcining) and particle size distribution for spray dried candidate materials after calcining at 1,200°C...... 80 Table 4.5. Thermodynamic predictions of slagging temperatures of candidate materials in air and inert environments with and without Na contamination in the Mn2O3 powder...... 87 Table 4.6. Kinetic parameters calculated for the best individual fitting of the experimental at β = 10.0°C/min...... 91 Table 4.7. Kinetic parameters calculated for the best individual fitting of the experimental data for two different regions...... 92

FIGURES Figure 1.1: Methods of concentrating solar irradiance using a) power tower and heliostats and b) a parabolic dish concentrator 7. c) A schematic of a generic two-step solar thermal water splitting cycle...... 2 Figure 1.2 Thermodynamic extent of oxygen non-stoichiometry (δ) of ceria, based on temperature and partial pressure of oxygen 26...... 11 Figure 2.1: (a) Thermodynamic extent of oxygen nonstoichiometry of ceria at 1773 K and as a function of pO2, (b) H2 and O2 production rates, cycled at 1773 K with pO2 = 10-5 atm and pH2O = 0.15 atm. reprinted from [13] ...... 28 Figure 2.2: (a) Total O2 and CO production by LSM50 and YSM50, cycled at 1573 K and 1673 K. reprinted from [15]. (b) H2 and O2 production rates by doped hercynite, cycled at 1623 K. Reprinted from [12] ...... 29 Figure 2.3: Equilibrium yield (Δδ) of ceria at Tred of 1773 K. The dashed line is for Tred of 1883 K. Reprinted from [18] ...... 31 Figure 2.4: a) Excess H2O/H2 (nwh) ratio values and b) excess inert gas/O2 (nio) ratio values, for ceria at Tred of 1,800 K. Reprinted from [20] ...... 32 Figure 2.5: An example of a process diagram used to calculate system efficiency. Reprinted from Ehrhart et al.[22] ...... 33 Figure 2.6: H2 capacity (Δδ) for ceria and ferrite/zirconia composite at Tred = 1600 K and pO2 = 0.1 Pa. Reprinted from [22] ...... 35 Figure 2.7: Inert gas to fuel (H2 or CO) ratio (RSG) for ceria reduction at Tred = 1773 K with the countercurrent flow and mixed flow arrangements. Reprinted from [28] ...... 37 Figure 2.8: ηSTH for inert gas sweep with various limits on the amount of inert gas using for ceria with 1,800 K reduction temperature and 0.1 Pa reduction pressure. Reprinted from [20] ...... 37 Figure 2.9: ηSTH values for ceria with 1,800 K reduction temperature and 0.1 Pa reduction pressure. (a) Various values of gas heat recuperation (εGG), 50% solid heat recuperation (εSS) and nio ≥ 100. (b) Various values of (εSS) and 90 % εGG. Reprinted from [20] ...... 40 Figure 2.10: The SurroundSun Reactor. Reprinted from [36] ...... 43 Figure 2.11: The isothermal reactor. Reprinted from [34]...... 44 Figure 2.12: The membrane reactor. Reprinted from [37] ...... 45 Figure 3.1 Mass loss versus time plots for hercynite reduction, carried out heating up to 1500 °C under an argon atmosphere ...... 55 Figure 3.2: conversion versus temperature plots for hercynite reduction, carried out at multiple heating rates ...... 56 Figure 3.3: Ea versus α calculated using KAS and Starink isoconversional methods...... 57 Figure 3.4. Comparison between the experimental TGA results at β = 5.0°C/min and calculated data using AE0.5, F3, D3 and P2 fitting models ...... 58 Figure 3.5: TGA experimental data and predictions with Avrami-Erofeev, AE0.5, model (α = 0 – 35%) and reaction order, F3, model (α > 35%) at different heating rates a) 5.0, b) 7.5, c) 10.0 and d) 12.5°C/min ...... 60 Figure 3.6. Schematic description of Avrami-Efrofeev family models ...... 61 Figure 3.7: X-ray diffraction spectra for calcined and reduced hercynite materials ...... 62

Figure 3.8: Mass loss versus temperature plots for reduction of calcined and oxidized (with H2O) hercynite materials at different heating rates a) 5°C/min, b) 10°C/min ...... 64 Figure 3.9: X-ray diffraction spectra for reduced and oxidized (H2O) hercynite materials ...... 64 Figure 4.1. SEM images of spray-dried particles before calcine: a) NS, b) Al30, c) Zr30, d) Fe67...... 78 Figure 4.2. SEM images of spray-dried particles after calcine at 1,200°C for 8 hours: a) NS, b) Al30, c) Zr30, d) Fe67...... 79 Figure 4.3. SEM images of Fe67 prepared by intensive mixing after calcine at 1,200°C for 8 hours: a) x < 25 µm, b) 100 < x < 500 µm ...... 80 Figure 4.4. X-ray diffraction spectra for spray-dried candidate materials after calcining at 1,200°C ...... 81 Figure 4.5. Thermodynamic predictions of reduction and oxidation behavior of candidate materials in air and inert environments...... 83 Figure 4.6. Thermogravimetric analysis for candidate active materials over six redox cycles, with oxidation at 650°C and reduction at 1,100°C, and 1,200°C. Plots at the top of each column show the temperature profile, and plots below show the specific mass change of the sample during redox cycling...... 85 Figure 4.7. Mass change for top performing candidate materials over six redox cycles. Theoretical maximum mass change for complete reduction is shown by solid lines...... 86 Figure 4.8. a) α versus temperature plots for oxidation of fe67 materials at multiple heating rates. b) Ea versus α calculated using KAS and Starink isoconversional methods ...... 89 Figure 4.9. X-ray diffraction spectra of Fe67 at reduced, 20% 50% and 100% oxidized states. (B = Bixbyite, (Mn,Fe)2O3, J = jacobsite, MnFe2O4) ...... 90 Figure 4.10. Comparison between the experimental TGA results at β = 10.0°C/min and calculated data using D3, F2, P2 and R3 fitting models ...... 91 Figure 4.11. TGA experimental data and predictions with kinetic order model at different heating rates a) 2.5, b) 5.0, c) 7.5 and d) 10.0°C/min ...... 93 Figure 4.12. α versus temperature plots for oxidation of two different particle sizes fe67 materials at 10˚C/min ...... 94 Figure 4.13. Schematic description of (a) diffusion family models and (b) Avrami-Efrofeev family models...... 95

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CHAPTER 1

1. INTRODUCTION

1.1. Motivation

Energy and environmental issues at a global level are important topics and to that extent focus has been on the generation of clean energy for some time. The use of renewable energy resources is essential to decrease greenhouse gas emissions responsible for climate change.

Carbon dioxide produced by conventional industrial processes is responsible for more than 50% of the man-made greenhouse effect 1. Concentrated solar technologies provide the option of converting solar energy into electrical, thermal and chemical forms 2,3.

Hydrogen is widely used as a feedstock in several energy demanding industries such as petroleum, chemicals, fertilizers and others. At present hydrogen is produced mainly from fossil fuels through methane steam reforming 4. Because of the nonrenewable nature and the large amounts of CO2 associated with the steam reforming/water gas shift process research, for a while now, focus has shifted to the development of new methods to produce hydrogen from water.

Solar thermochemical water-splitting is a promising method for producing hydrogen which uses the abundant solar energy as an energy source 5.

1.2. Solar Thermochemical Water Splitting

Solar thermochemical water splitting uses concentrated sunlight from mirrors that can be configured in a variety of ways, as shown in Figure 1.1. The collected solar energy is focused on a reactor, heating it to high temperatures to drive the endothermic splitting of H2O into H2 and

O2. Direct thermolysis is a single-step process where water is decomposed to H2 and O2 gases.

Although the process appears simple, it is unfeasible because of the high reaction temperatures

(~2,200°C) required for even insignificant extents of reaction 6. Additionally, high-temperature

H2/O2 separation steps are required to prevent product recombination and an explosive mixture.

Figure 1.1: Methods of concentrating solar irradiance using a) power tower and heliostats and b) a parabolic dish concentrator 7. c) A schematic of a generic two-step solar thermal water splitting cycle.

Water splitting can be divided into two or more steps in which the H2 and O2 are produced separately, thus avoiding the issues of high-temperature gas separations 8, but these reaction cycles typically come with other challenges. Two-step thermochemical water splitting cycles rely on the reduction and subsequent re-oxidation of metal oxides and require reduction temperatures greater than 1,000°C 6,9-11. Multistep cycles, with two steps and more, can operate at a maximum temperature below 900°C. However, these cycles typically utilize a metal in conjunction with harsh acids or bases and often include an electrolysis step 8,12-19. Hazardous chemicals, complicated process designs, and compounding inefficiencies from numerous process steps

make multi-step cycles unlikely to achieve the high efficiencies required for economical H2 generation 6,9.

In two-step STWS, a metal oxide is heated under low oxygen partial pressure to a high temperature (TRED) by concentrated sunlight to reduce and generate O2, as shown in Equation

(1.1), where δ is the extent of reduction of the redox material, MOx is the oxidized state of a metal oxide in which δ = 0, and MOx-δ is the reduced state of a metal oxide, which has δ metal oxides per X oxygen molecules in the original oxide. The value of δ depends on the material and operating conditions. In the second step, the reduced metal oxide reacts with steam to re-oxidizes the material and forms H2, as shown in Equation (1.2). The two half-reactions form a full redox cycle, shown schematically in Figure 1.1c. Oxidation reaction has traditionally been carried out at

6,20-27 a temperature (TOX) that is at least 500°C lower than TRED ; this is indicated in the schematic in Figure 1.1c. However, it was shown that oxidation reaction can occur at temperatures up to and including the reduction temperature 28-32.

훿 (1.1) M푂 → M푂 + 푂 푥 푥−훿 2 2

M푂푥−훿 + 훿퐻2푂 → M푂푥 + 훿퐻2 (1.2)

1.3. Two-Step STWS Active Materials

The identification of active and robust materials that efficiently undergo redox reactions to drive STWS at practical conditions and reaction rates is an area of substantial research 7,33. The ideal STWS material has high specific H2 production capacity, low reduction reaction temperature, fast kinetics, a long lifetime, compatibility with containment materials, non-toxic composition, and low cost. The first two desirable characteristics are thermodynamic properties of the redox material, which, together with fast kinetics, are the major attributes that determine

the overall efficiency of the system. The other desirable characteristics affect the costs and potential hazards of operating a STWS system based on a particular redox material.

1.3.1. Thermodynamics of STWS Materials

The two reactions that make up a redox cycle can combine into a net H2O splitting reaction.

The overall energy input and entropy gain of a two-step STWS redox cycle must be at least that of direct water splitting, ΔH ≥ 286 kJ/mol and ΔS ≥ 44.4 J/mol∙K. The oxidation and reduction reactions must each be spontaneous (ΔG < 0). Based on these requirements, both the individual reaction steps and the overall STWS cycle are governed by a number of thermodynamic relationships (Equations (1.3)-(1.6)), in which the subscripts WS and TR indicate the water splitting (oxidation) reaction and the thermal reduction reaction, respectively.

1 ∆퐺 = ∆퐻 − 푇 (∆푆 + 푆푂2 ) ≤ 0 푇푅,푇푇푅 푟푒푑 푇푅 푟푒푑 2 푇푇푅 (1.3)

∆퐺 = −∆퐻 − ∆퐻퐻2푂 − 푇 (−∆푆 + 푆퐻2 − 푆퐻2푂) ≤ 0 (1.4) 푊푆,푇푊푆 푟푒푑 푓,푇푊푆 푊푆 푟푒푑 푇푊푆 푇푊푆

∆퐻푐푦푐푙푒 = ∆퐻푇푅 + ∆퐻푊푆 ≥ 286 푘퐽/푚표푙 (1.5)

∆푆푐푦푐푙푒 = ∆푆푇푅 + ∆푆푊푆 ≥ 44.4 퐽/푚표푙 퐾 (1.6)

Equation (1.4) states that the oxidation reaction must be exothermic (ΔHWS < 0) because the overall H2O splitting step is entropically unfavorable (ΔS < 0) and both reactions must be exergonic (ΔG < 0). The entropy decrease of the oxidation reaction step arises because the entropy loss in reducing H2O to H2 (ΔS0 ≈ -58 J/mol∙K) is greater than any possible entropy gain

21 from re-oxidizing the STWS redox materials . The exothermic oxidation reaction (ΔHWS < 0) thus requires the thermal reduction step must be endothermic by at least 286 kJ/mol in order to satisfy the overall energetic requirements of H2O splitting, as shown in Equation (1.5). Hence, materials with reduction enthalpies <286 kJ/mol will not split H2O. This explains why some

materials (e.g., Co3O4 and CdO) which have the desirable property of reducing at relatively low

34,35 temperatures do not re-oxidize with H2O and therefore do not drive STWS . Conversely, materials with a highly exothermic oxidation readily split H2O but have correspondingly large endothermic reduction enthalpies. Thus, these materials only undergo reduction at very high

34,35 temperatures, as observed for WO3 or Nb2O5 . This can be explained by a simple examination of the Gibbs free energy equation: ΔG = ΔH – T·ΔS. Assuming a near-constant ΔS (which most thermal reduction of metal oxides have), a larger ΔH value will require a larger T value in order to still make the overall reaction spontaneous (ΔG<0). Additionally, when re-oxidation of the material is highly exothermic, recovering the released heat is not possible, leading to a less efficient process. Therefore, an ideal material is one where the reduction reaction is sufficiently endothermic to drive the water splitting reaction, but not so endothermic as to require impractical reduction temperatures.

1.3.2. Current STWS Materials

Currently, the two-step water splitting redox cycles can be categorized by their reaction mechanisms: volatile stoichiometric chemistries, non-volatile stoichiometric chemistries, or oxygen vacancy chemistries. The two stoichiometric mechanisms involve the generation of a stoichiometric quantity of oxygen (0.5 moles) and hydrogen (1 mole) for each mole of reacting metal oxide as it undergoes reduction or oxidization, respectively. Both stoichiometric chemistries are decomposition reactions which produce either gaseous products, as in the volatile

36 stoichiometric chemistries (e.g., ZnO → Zn(g) + ½O2 ), or solid products with an altered crystal

23 structure, as in the non-volatile stoichiometric chemistries (e.g., Fe3O4 → 3FeO + ½O2 ) in the reduction step. O-vacancy chemistries release O2 by the O-vacancies formation in the metal

37 oxide lattice (e.g., CeO2 → CeO2-δ + δ/2 O2 ), while the overall crystal structure of the solid

remains unchanged. Generic chemical reactions for each of these mechanisms are shown in

Equations (1.7)-(1.9)

1 (1.7) M푂 → M + 푂 (푠) (푔) 2 2 1 (1.8) M푂 → M푂 + 푂 푥(푠1) (푠2) 2 2 1 (1.9) M푂 → M푂 + 푂 푥(푠1) 푥−훿(푠2) 2 2

Most of the early STWS redox cycles were based on stoichiometric chemistries, but more recently the focus of research efforts has shifted to O-vacancy based mechanisms. The review below briefly highlights research advances for each of these mechanisms, along with general descriptions of the benefits and drawbacks to each.

1.3.2.1. Volatile Stoichiometric Chemistries

STWS volatile stoichiometric redox cycles offer high specific H2 production capacity, though generally with some operational challenges. Volatile stoichiometric cycles are attractive as they offer high specific H2 production capacities. For example, BeO has the highest theoretical H2 production capacity of any redox material, with just under 40 mmol of H2/g of BeO. All of the material in volatile stoichiometric cycles is active (participates in the redox cycle) and no excess mass stabilizes the reduced material as a condensed phase. This requires difficult gas handling steps, especially quenching of the reduction product gases to separate the reduced redox material

7 from the liberated O2 and preventing the reverse re-oxidation . After the reduced material solidifies, further processing steps are required to transport the reduced solid material out of the quenching zone and into the oxidation reactor. Despite these challenges, two volatile

36,38 stoichiometric redox cycles are still being studied, the zinc oxide and tin oxide cycles .

The ZnO/Zn system (shown in Equations (1.10) and (1.11)) was an early promising STWS redox cycle for splitting water 36. Thermal reduction of ZnO at atmospheric pressure requires

39 high temperatures (~1,700-2,000°C) with air, but lowering the O2 partial pressure via vacuum pumping or the use of an inert sweep gas decreases the reduction temperatures to ~1,300°C 40,41.

40,42-44 However, this lower reduction temperature decreases reaction rate . Oxidation with H2O can be done with solid, liquid, and gaseous Zn, although the reaction with either liquid or gaseous Zn is significantly faster than with solid Zn 40,45-47.

1 (1.10) 푍푛푂 → 푍푛 + 푂 (푠) (푔) 2 2 푍푛(푔) + 퐻2푂 → 푍푛푂(푠) + 퐻2 (1.11)

While high reduction temperatures and a slow reduction rate are detrimental to efficient

STWS process, the most challenging impediment to efficient hydrogen generation is the back- reaction of Zn(g) to ZnO(s) with the released O2 on cooling of the reduction product stream. This reaction is thermodynamically favored with fast kinetics 48 This requires rapid quenching of the produced gases. In addition to the significant improvements needed to the quenching step, transport of the reduced and oxidized materials (which often deposit on the walls of the quenching or oxidization reactors) will have to be considered if the ZnO/Zn redox cycle is to become a viable STWS system.

Similar to ZnO, SnO2 dissociates to form SnO and O2 (as seen in Equations (1.12) and

(1.13)), but at a more practical temperature (~1,200°C at low oxygen partial pressure) than ZnO reduction. However, unlike ZnO which forms metallic Zn, SnO2 decomposition produces gaseous SnO. Further reduction to form Sn metal is possible, but undesirable due to higher reduction temperatures, additional reaction steps 49, faster oxidation kinetics, and fewer oxidation competing reactions 50.

1 (1.12) 푆푛푂 → 푆푛푂 + 푂 2(푠) (푔) 2 2 푆푛푂(푔) + 퐻2푂 → 푆푛푂2(푠) + 퐻2 (1.13)

The SnO2/SnO cycle has many advantages over the ZnO/Zn cycle, but some critical challenges remain. SnO condenses at 1,527°C while Zn condenses at 907°C, meaning a slower

38 quench rate can be employed to limit gas phase re-oxidation during SnO/O2 separation .

Additionally, the undesirable re-oxidation of SnO(s) by O2 is slower than the re-oxidation of Zn(s), with a Zn re-oxidation reaction which is roughly twice as fast as the SnO re-oxidation reaction 48.

38,51,52 Furthermore, water almost completely re-oxidizes SnO back to SnO2 , significantly higher

51 than the re-oxidation of Zn, albeit at a slower rate . While the SnO2/SnO STWS cycle appears to be more promising than the ZnO/Zn cycle, the SnO2/SnO cycle faces major challenges such as low recovery of the reduced material and the difficulties inherent in quenching the reduction product and handling the resulting reduced solids.

1.3.2.2. Non-Volatile Stoichiometric Reactions

Ferrite is an attractive redox material for STWS because of its relatively high theoretical H2 production capacity (~4,300 μmol/g) and the absence of a volatile reduced metal oxide. The first two-step non-volatile metal oxide redox cycle was developed by Nakamura and it was based on

2+/3+ the oxidation and reduction of Fe as it transitions between magnetite (Fe3O4) and wüstite

23 (FeO) . The high reduction temperature of Fe3O4 at ~2,200°C under atmospheric conditions can

11 be lowered to 1,300-1,400°C at reduced O2 partial pressures . However, low melting temperature of Fe3O4 (~1,700°C) and FeO (~1,350°C) presents challenges during the reduction step 11,23,53. Operating the reduction step at temperatures close to the melting point leads to extensive sintering of the active materials which causes loss of surface area available for reaction

54 . This in turn leads to low yields of the oxidized Fe3O4 from the transport-limited steam oxidation reaction of FeO 5,55. These factors complicate the design and operation of STWS reactors based on the Fe3O4/FeO redox cycle. Two modifications have been suggested to

overcome the deficiencies of the Fe3O4/FeO redox cycle: introduction of an inert carrier or buffer to minimize sintering and doping Fe3O4 to lower the reduction temperature of the oxidized phase and/or to raise the melting temperature of the reduced phase. Inert supports such as silica particles 56 and yttrium stabilized zirconia (YSZ) have been tried, but these materials either did not do enough to prevent the slow steam oxidation kinetics. In the second suggested approach,

Fe3O4 is doped with many different elements (Zn, Sn, Mn, Co, Ni, and combinations thereof) in an attempt to lower the reduction temperature to prevent sintering and increase the melting temperatures of the reduced species 57-62. Zn and Sn dopants form separate solid phases and Zn sublimes and deposits on the reactor walls 7,57,60. Mn dopants lower the oxidation reaction rate

58 with no corresponding increase in specific H2 production capacity . Co and Ni dopants show

59 promise, as the reduction products melt at temperatures higher than pure Fe3O4 (>125˚C) .

However, techniques to prevent sintering of the reduced product, such as the use of a support, are required. Adding an inert support lowers the specific hydrogen production capacity by adding to the thermal mass of the system.

1.3.2.3. Oxygen Vacancy Mechanism Reactions

Oxygen vacancy STWS cycles tend to have faster reaction rates and fewer problems associated with phase change, but typically have much lower H2 production capacities. In contrast to the stoichiometric STWS reaction mechanism described above, redox materials operating through the O-vacancy mechanism do not change its phase throughout reduction and oxidation reactions. The O2 released during reduction results from the formation of oxygen vacancies within the material. Therefore, these cycles represent incomplete reduction of the active materials in potentially stoichiometric reactions. In other words, the amount of O liberated is insufficient to drive complete decomposition of the oxidized phase to a new reduced phase at

the reduction temperatures employed. The materials involved in these redox cycles, in general, can drive H2O splitting at conditions where they do not suffer melting or formation of gaseous reduced products. Consequently, handling the reduced materials produced by the O-vacancy mechanism is simpler than handling redox materials produced by stoichiometric chemistry mechanisms. However, the specific H2 production capacities of O-vacancy mechanism materials are generally lower than those of stoichiometric chemistries because only a fraction of the metal oxide participates in the redox process.

In O-vacancy mechanism STWS cycles, the relevant measure of the activity is the change in the extent of O non-stoichiometry between the oxidation and reduction steps (Δδ), as shown in

Equations (1.14)-(1.16). The extent of non-stoichiometry is determined by the temperature, the

O2 or H2O partial pressure operating conditions of the individual reaction steps, and the degree to which the thermodynamic equilibrium is achieved. An example is illustrated graphically in

Figure 1.2, which shows the O non-stoichiometry for CeO2 at various temperatures and O2 partial pressures. As this figure demonstrates, redox cycles can operate isothermally, isobarically, or by changing both temperature and O2 partial pressure. The amount of non- stoichiometry achieved for a given set of operating conditions is material dependent.

∆훿 (1.14) M푂 → M푂 + 푂 푥−훿표푥 푥−훿푟푒푑 2 2

M푂푥−훿푟푒푑 + ∆훿퐻2푂 → M푂푥−훿표푥 + ∆훿퐻2 (1.15)

∆훿 = 훿푟푒푑 − 훿표푥 (1.16)

1.3.2.3.1. The Ceria-Based Cycle

Cerium(IV) oxide (CeO2 or ceria) is a material that undergoes an oxygen vacancy redox mechanism cycle and has a number of benefits. The originally proposed cycle was the reduction of CeO2 to Ce2O3, but the required reduction temperature for complete reduction (>2,000°C) is close to the melting temperature of Ce2O3, which led to sintering and substantial evolution of

gaseous Ce 63. Kaneko et al. suggested that ceria could function as an O-vacancy mechanism

STWS redox material after testing various mixed-metal cerium oxides 64. Chueh et al. were the first to suggest un-doped ceria as an O-vacancy mechanism STWS redox material and found that

25 ceria produced ~379 μmol H2/g when reduced at 1,500°C and oxidized at 800°C . Ceria also benefits from rapid reduction reaction kinetics, which is limited by the heating rates of the reactor. Additionally, ceria has been shown to be stable over hundreds of cycles 20,25 and is capable of undergoing isothermal water splitting 30,31. Many works 65-67 have quantified the thermodynamics of ceria over a wide range of temperatures and pressures, as shown in

Figure 1.2. However, the practicality of pure ceria in STWS applications is limited by the high reduction temperatures (>1,500°C) required to produce substantial quantities of H2.

Figure 1.2 Thermodynamic extent of oxygen non-stoichiometry (δ) of ceria, based on temperature and partial pressure of oxygen 26.

Research efforts have focused on doping ceria with many elements in an attempt to increase

68-70 the H2 production capacity and lower the required reduction temperature. Divalent and

trivalent 64,68,71-73 dopants have not achieved these goals. The di- and trivalent element dopants decrease the oxygen vacancy formation enthalpy to such an extent that the oxygen vacancies no

+ longer have the energy required to split water. Some tetravalent (4 oxidation state) elements have proven to be successful at increasing the H2 production capacity of ceria. While some

4+ 4+ 71 4+ 4+ dopants (Sn and Ti ) form phases inert to STWS , Zr and Hf dopants increase the STWS capacity of ceria but decrease the oxidation rate 74,75. Tetravalent dopant ions that are physically

4+ smaller than Ce improve STWS by inducing lattice strain, rather than changing oxidation states

76 4+ 4+ . The tensile strain imposed by doping Zr and Hf counteracts the compressive strain of forming an oxygen vacancy, thus decreasing the overall energy required to break the O-Ce bonds

4+ 4+ to form the vacancy. For Zr and Hf , the decrease in O-vacancy formation energy is sufficient to facilitate reduction, but not so large as to hinder water splitting (oxidation).

Additional dopants (Mg, Ca, Ni, Fe, and rare earth elements) have been incorporated into

77-80 Ce1-xZrxO2 in attempts to further increase H2 yields . Of these elements, Ni and Fe had no

78 effect on H2 production capacity, while Ca and Mg both increased H2 yields . Co-doping Pr, La,

80 and Tb produced more H2 than single-doped Ce0.75Zr0.25O2 . The benefit of including a second dopant is potentially attributable to changes in the oxygen vacancy formation energy from a

4+ 76 slight modification to the reducibility of the Ce ions or to alterations in the Zr-induced strain field by the variously sized lanthanides. Additionally, La and Gd were found to increase cycling stability of the doped ceria 77.

Of the other ceria dopants examined, W was found to not facilitate STWS 81. However, U was found to increase H2 production capacity, either due to its ability to enable over-oxidation,

82 4+ i.e. Ce1-xUxO2+y , or its ability to take on multiple oxidation states which then aid Ce reduction

76,83. While U is unlikely to be used in commercial processes due to the radioactivity nature of its various isotopes, it may serve as a useful tool for identifying other dopants.

Despite the extensive effort to dope ceria to achieve better STWS materials, the relatively low specific H2 production capacity at reasonable reduction temperatures (≤1,500°C) still limits its potential application in commercial STWS processes. Either very efficient heat recuperation is needed so that ceria can be repeatedly cycled efficiently, or new dopants from the small list of elements not already studied must be identified to either lower the reduction temperature, increase H2 production, or preferably both.

1.3.2.3.2. Perovskite Cycles

Perovskites are a broad set of materials having the formula ABO3 which is highly amenable to doping, composed of many different elements, and stable at relatively high levels of oxygen non-stoichiometry. These characteristics led Nalbandian et al. and Evdou et al. to suggest perovskites as oxygen exchange materials in a high temperature methane membrane reactor and

84,85 in two-step chemical looping cycles . This prompted Scheffe et al. to suggest using LaxSr1-

86 xMnO3 (SLM) in STWS redox cycle , which was followed soon thereafter by McDaniel et al.

87 who used a slightly modified LaxSr1-xMnyAl1-yO3 (SLMA) perovskite . Both the SLM and

SLMA materials have more H2 capacity than ceria at low temperatures; where SLMA produced

2.3 times the amount of H2 after reduction at 1,350°C (307 μmol/g) as ceria produced after reduction at 1,500°C 86,88.

Doping the perovskite structure with other elements led to a variety of effects and tradeoffs.

The SLM materials appear to suffer from sintering issues, while the SLMA material produced

86,87 3+ consistent quantities of H2 over 80 cycles . It was suggested that Al acts to stabilize the

SLMA perovskite and prevent sintering. While doping the B-site stabilized the SLMA materials,

doping the A-site with 10-40% Sr increased the overall H2 productivity of the SLM materials

89 from 40.6 to 397.7 µmol of H2/g . However, similar to other STWS materials, the increased H2 production capacity was coupled with a decreased reaction rate 89.

La- and Fe-based perovskites have also been tested for solar thermal gas splitting capabilities, namely LaxA1-xFeyB1-y (A= Sr, Ce and B=Co, Mn). Although these materials evolved significant quantities of O2 during reduction, almost no gas splitting behavior was observed. This is because the low reduction enthalpies, as calculated by Deml et al. 90, are insufficient to reduce water. While these perovskites were incapable of STWS, CO2 splitting

71 does occur when these materials are supported on SiO2 . This suggests that a reaction occurs between the SiO2 support and the perovskite, producing a material with a reduction enthalpy sufficiently high to reduce CO2.

Non-La based perovskites can also potentially undergo STWS; McDaniel et al. showed that

88 CaTi1-xFexO3 has similar O exchange behavior as CeO2 , and Demont et al. showed that BaySr1-

91 yCoxFe1-x splits water, although with a lower H2 production capacity than LaySr1-yMnO3 . This suggests that the SLM materials are just a starting point, and new perovskites with higher H2 production capacities are possible. The only major drawback to using perovskites identified so far is their relatively high heat capacity 86.

1.3.2.3.3. The Hercynite Cycle

In 2010, Scheffe et al. discovered that when cobalt ferrite was deposited on alumina it would produce H2 after reduction at 1,200°C, which is 200-300°C lower than when cobalt ferrite was deposited on a zirconia support 92. This redox cycle was initially hypothesized to operate through a stoichiometric mechanism, where the CoFe2O4 reacts with the Al2O3 support during reduction to produce a solid solution of FeAl2O4 (hercynite) and CoAl2O4: CoFe2O4 + 3Al2O3 →CoAl2O4

+ 2FeAl2O4 + ½ O2. This solid solution was expected to then revert back to the starting two separate phases upon oxidation by steam 92. However, it has been shown later through DFT calculations that hercynite and cobalt-doped hercynite materials operate through an oxygen vacancy mechanism 93.

92,94 In addition to producing H2 at relatively low reduction temperatures , on-sun experiments have demonstrated that the doped-hercynite material produces ~10 times more H2 produced and

54 does not sinter, in contrast to Fe3O4 materials . However, at reduction temperatures above

92 1,500°C, CoFe2O4 produces more H2 per gram of active material than doped-hercynite because a larger fraction of the material undergoes active reduction and oxidation.

Doped-hercynite active materials not only reduce at relatively low temperatures, but they are also capable of producing substantial quantities of H2 isothermally; operating isothermally at

1,350°C, the doped-hercynite material generated >12 times more hydrogen than ceria after reduction at 1,350°C and oxidation at 1,000°C 28. The larger extent of re-oxidation at the higher water splitting oxidation temperatures is attributed to the kinetic limitations of the re-oxidation of doped-hercynite at lower temperatures. Similar to other STWS materials, the rate-limiting step of the doped-hercynite oxidation half-cycle is attributed to surface reaction 95. For doped-hercynite active materials, slow reaction rates are the most significant limitation to the productivity and overcoming the slow kinetics of the surface reactions of O2 generation and H2O spitting during the reduction and oxidation half-cycles, respectively, is the major challenge to improving this material.

1.4. Project Objectives

The objective of this research is to contribute towards understanding the redox reaction mechanism of spinel materials for solar thermochemical water splitting and energy storage, with

three specific aims: 1.) contribute towards a better understanding of the reaction mechanism of the hercynite cycle; 2) Develop a detailed kinetic model of the hercynite reduction reaction for solar thermochemical water splitting; 3) Develop a detailed kinetic model of the iron manganese oxidation reaction for solar thermochemical energy storage.

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CHAPTER 2

2. ISOTHERMAL REDOX FOR H2O AND CO2 SPLITTING – A REVIEW AND

PERSPECTIVE

2.1. Abstract

Solar thermal splitting of water or carbon dioxide is a promising technology for producing hydrogen or carbon monoxide. In a two-step cycle, a metal oxide is thermally reduced with concentrated solar radiation to release oxygen. The reduced metal oxide is then re-oxidized with steam or carbon dioxide to produce hydrogen or carbon monoxide. The two-step redox cycle can be operated either as a temperature swing where there is a temperature difference between the reduction and oxidation steps or isothermally. This review article discusses various aspects of operating the redox cycle isothermally including redox cycle thermodynamics and overall system efficiency and describes solar reactor concepts based on isothermal operation.

2.2. Introduction

Two-step solar thermochemical redox cycles provide a renewable energy driven route for producing synthesis gas (H2 and CO). The cycles utilize the abundant solar energy to provide the energy required for water splitting (WS) and carbon dioxide splitting (CDS) cycles. In a two-step solar thermochemical redox cycle, a metal oxide is first heated by concentrated solar energy to

undergo reduction and generate O2 as shown in equation (2.1), where MOx−δOX is the oxidized

state and MOx−δRED is the reduced state of the metal oxide. In the second step, the reduced metal oxide is reacted with H2O and/or CO2 to produce H2 and/or CO as shown in equations (2.2) and

(2.3). The amount of H2 and/or CO produced is given by the difference in non- stoichiometry (δ) between the reduction and oxidation thermodynamic states (Δδ = δ푅퐸퐷 − δ푂푋) of the metal oxide.

훥훿 푀 푂 → 푀 푂 + 푂 푦 푥−훿푂푋 푦 푥−훿푅퐸퐷 2 2 (2.1)

푀푦푂푥−훿푅퐸퐷 + 훥훿퐻2푂 → 푀푦푂푥−훿푂푋 + 훥훿퐻2 (2.2)

푀푦푂푥−훿푅퐸퐷 + 훥훿퐶푂2 → 푀푦푂푥−훿푂푋 + 훥훿퐶푂 (2.3)

2.3. Chemical thermodynamics

The first step in the redox cycle requires high temperatures (1473 K – 1773 K) to drive the highly endothermic reaction [1]. In the past, researchers have carried out the second step, the oxidation reaction, at temperatures lower than the reduction temperature (~ ΔT > 400 K) to split

H2O and/or CO2 [2-8]. Traditionally, the two-step redox cycle was analyzed thermodynamically as a closed system [8-11]. For a closed system, the Gibb’s free energy for the reduction and oxidation reactions that dictates the favorable conditions required for the spontaneity of the reactions is given by Equations (2.4) and (2.5) [8, 12].

1 ∆퐺 = ∆퐻 − 푇 (∆푆 + 푆푂2 ) ≤ 0 푇푅,푇푇푅 푟푒푑 푇푅 푟푒푑 2 푇푇푅 (2.4)

∆퐺 = −∆퐻 − ∆퐻퐻2푂 − 푇 (−∆푆 + 푆퐻2 − 푆퐻2푂) ≤ 0 (2.5) 푊푆,푇푊푆 푟푒푑 푓,푇푊푆 푊푆 푟푒푑 푇푊푆 푇푊푆

Where ΔG is the Gibb’s free energy change for the thermal reduction (TR) reaction and water splitting reaction, respectively. ΔHred and ΔSred are the enthalpy change and entropy change between the reduced and oxidized metal oxide, respectively, T is the temperature in Kelvin, S is

퐻2푂 the entropy and ∆퐻푓 is the enthalpy of formation of water. Setting equations (2.4) and (2.5) equal to zero will provide a required temperature difference between the reduction and oxidation steps as shown in equation (2.6).

퐻2푂 −2∆퐺푓,푇 − 푇푊푆훥푆 ∆푇 = 푊푆 (2.6) 푆푂2 + 2∆푆 푇푇푅 푟푒푑

Where ΔT = TTR – TWS, ΔS is the entropy increase of O2 as it is heated from oxidation to

퐻2푂 reduction temperatures and ∆퐺푓 is the Gibb’s free energy of formation of H2O. Therefore, analyzing the two-step thermochemical cycle as a closed system requires a temperature difference between reduction and oxidation steps. This closed system thermodynamic analysis of the two-step-redox reactions is thorough if reactant and product gases are not removed from the system [12]. However, solar thermal reactors are designed to remove generated O2 and H2 and unreacted H2O from the reactor system continuously. Therefore, Muhich et al. have demonstrated thermodynamically that the oxidation reaction can be run isothermally (ΔT = 0 K) by analyzing the redox cycle as an open system [12]. The oxidation reaction will proceed spontaneously to the right when the Gibb’s free energy of the reactants is larger than those of the products as shown in equation (2.7).

−푇푂푋 (푆퐻 푂 + 푆푀 푂 ) + 휇퐻 푂푁퐻 푂 + 휇푀 푂 푁푀 푂 2 푦 푥−훿푅퐸퐷 2 2 푦 푥−훿푅퐸퐷 푦 푥−훿푅퐸퐷 (2.7)

> −푇 (푆퐻 + 푆푀 푂 ) + 휇퐻 푁퐻 + 휇푀 푂 푁푀 푂 2 푦 푥−훿푂푋 2 2 푦 푥−훿푂푋 푦 푥−훿푂푋

Where µ is the chemical potential and N is the number of species of H2O, 푀푦푂푥−훿푅퐸퐷 , 푀푦푂푥−푂푋 and H2. Rearranging equation (2.7) will result in the total chemical potential of H2O required to drive the reaction forward at any temperature as shown in equation (2.8).

휇퐻 푂푁퐻 푂 > −푇푂푋 (푆퐻 + 푆푀 푂 − 푆퐻 푂 − 푆푀 푂 ) + 휇퐻 푁퐻 2 2 2 푦 푥−훿푂푋 2 푦 푥−훿푅퐸퐷 2 2 (2.8)

+ 휇푀 푂 푁푀 푂 + 휇푀 푂 푁푀 푂 푦 푥−훿푂푋 푦 푥−훿푂푋 푦 푥−훿푅퐸퐷 푦 푥−훿푅퐸퐷

Therefore, the high chemical potential of H2O and low chemical potential of H2 will drive the oxidation reaction forward. Similar analysis can be applied to the reduction reaction, which will result in the total chemical potential of O2 required to drive the reaction forward as shown in equation (2.9).

휇푂 푁푂 < 휇푀 푂 푁푀 푂 − 휇푀 푂 푁푀 푂 − 푇푇푅(푆푀 푂 2 2 푦 푥−훿푂푋 푦 푥−훿푂푋 푦 푥−훿푅퐸퐷 푦 푥−훿푅퐸퐷 푦 푥−훿푂푋 (2.9) − 푆푀 푂 − 푆푂 ) 푦 푥−훿푅퐸퐷 2

The chemical potential of O2, H2O and H2 gases is controlled by the partial pressure of gases in the system which allows for the isothermal operation of the cycle. This can be done in open systems by removing the generated O2 and H2 continuously and ensuring high partial pressure of

H2O and/or CO2 in the oxidation step [12].

Cerium oxide is considered one of the most promising redox materials for solar thermochemical H2O and/or CO2 splitting. Isothermal redox cycling of cerium oxide for H2O splitting has been demonstrated thermodynamically and experimentally by Hao et al. [13].

Figure 2.1 (a) shows thermodynamic H2 (Δδ) production under isothermal conditions, which is a result of the change in O2 chemical potential between the reduction and oxidation steps.

Figure 2.1 (b) shows the isothermal experimental O2 and H2 production rates carried out at 1773

(a)

(b)

Figure 2.1: (a) Thermodynamic extent of oxygen nonstoichiometry of ceria at 1773 K and as a function of pO2, (b) H2 and O2 production rates, cycled at 1773 K with pO2 = 10-5 atm and pH2O = 0.15 atm. reprinted from [13]

Perovskites are another type of promising redox materials that are capable of solar thermochemical H2O and/or CO2 splitting. Perovskites have the general form of ABO3 and they are highly amenable to doping on the A and B cation sites [1, 14]. Deyer et al. demonstrated an isothermal CO2 splitting by La0.5Sr0.5MnO3 (LSM50) and Y0.5Sr0.5MnO3 (YSM50) perovskites materials as shown in Figure 2.2 (a) [15]. Muhich et al. also demonstrated the isothermal cycle with doped hercynite materials for WS redox as shown in Figure 2.2 (b) [12].

(a)

(b)

Figure 2.2: (a) Total O2 and CO production by LSM50 and YSM50, cycled at 1573 K and 1673 K. reprinted from [15]. (b) H2 and O2 production rates by doped hercynite, cycled at 1623 K. Reprinted from [12] 2.4. Isothermal vs. non-isothermal

The thermal reduction reaction is favored by high temperatures and low oxygen partial pressures, while the oxidation reaction is favored by lower temperatures and high partial pressure of H2O and/or CO2. A major challenge for operating the cycle non-isothermally (i.e. temperature-swing) is the solid-solid heat recuperation as the reactive materials cycle between reduction and oxidation reaction temperatures. As the temperature difference (ΔT) increases, the energy required to reheat the reactive solids increases. Therefore, effective solid-solid heat recuperation is identified as a key parameter for an efficient process [4]. However, implementing

solid-solid heat recovery remains a major challenge as it may involve complex solids flow at high temperatures. A number of reactor concepts have been proposed to recover solid-solid heat, but they have yet to be successfully demonstrated in a working reactor [1, 16].

Operating the cycle isothermally eliminates the need for solid-solid heat recuperation, resulting in process design simplifications [13]. Also, operating isothermally (ITS) will limit thermal stress and fatigue on the active and containment materials when compared to temperature-swing operation (TS) [1]. Additionally, ITS may potentially eliminate the process downtime take to reheat and cool the active materials between oxidation and reduction temperatures if carried out batch wise [17]. The advantage that isothermal operation provides, especially for kinetically limited reactive materials, is faster kinetics when compared to temperature swing operation for equivalent reduction temperatures. Muhich et al. reported an increase in H2 production by more than three times under isothermal conditions when compared to temperature swing run (ΔT = 300 K) with doped hercynite materials [12].

However, isothermal operation presents challenges as well. Lower O2 and higher H2O partial pressures are required to drive the reduction and oxidation reactions compared to those required by the temperature swing cycle [1]. Also, the thermodynamic fuel capacity (H2 and/or

CO) yield of the reactive material (Δδ) will decrease as ΔT approaches zero (isothermal) as shown in Figure 2.3 [18]. Ermanoski et al. assessed the isothermal cycle thermodynamically and found that a large amount of excess steam is required to reoxidize any reactive materials [19] as shown in Figure 2.4 (a). Furthermore, the required amount of inert gas to sweep generated O2 from the reduction reaction increases as ΔT approaches zero as shown in Figure 2.4 (b) [20].

Therefore, gas-gas heat recuperation between feed and product streams becomes more significant for the isothermal cycle.

Figure 2.3: Equilibrium yield (Δδ) of ceria at Tred of 1773 K. The dashed line is for Tred of 1883 K. Reprinted from [18] a)

Figure 2.4: a) Excess H2O/H2 (nwh) ratio values and b) excess inert gas/O2 (nio) ratio values, for ceria at Tred of 1,800 K. Reprinted from [20] Muhich et al. proposed a near-isothermal operation of the cycle as a trade-off between the isothermal and temperature-swing cycles. For this, the two-step redox cycle can be categorized by the temperature difference (ΔT), where ΔT=0 K for the isothermal cycle, 0> ΔT >150°C for the near-isothermal cycle and ΔT >150 K for a temperature-swing cycle [1].

2.5. Solar to H2/CO thermodynamic process efficiency model

The overall solar-to-fuel energy conversion efficiency (ηSTF) is a crucial measure in evaluating the performance of the two-step thermochemical cycle. Therefore, it is important to analyze the entire process to determine the effects of various parameters on the process efficiency. The efficiency calculations typically use a process diagram to illustrate energy sinks and sources that exist in the two-step thermochemical process. An example of a process diagram is shown in Figure 2.5. Although the two redox thermochemical cycle may look simple, there are

many factors that affect ηSTF calculations. These factors can be classified into factors that are related to the redox materials and factors that are related to the reactor design including operational and design parameters. For solarthermal water splitting, ηSTF calculations are typically performed as a function of ΔT and the reduction partial pressure (pred) to determine the optimal mode of operation in terms of ΔT (isothermal, near-isothermal or temperature-swing) and pO2 [18-26].

Figure 2.5: An example of a process diagram used to calculate system efficiency. Reprinted from Ehrhart

et al.[22]

2.5.1. Materials and kinetics effect

Most of the solar-to-fuel analysis used cerium oxide as the active materials [6, 26-29]. This is because the thermodynamic end states of cerium oxide (δ) have been experimentally determined by Panlener et al. as a function of temperature and pO2 [30]. Nonetheless, the results found for ceria may not necessarily hold for other materials [22]. Ehrhart et al. compared two different redox materials (cerium oxide and ferrite/zirconia composite) [22]. Cerium oxide is characterized by its fast kinetics and lower fuel productivity, whereas the ferrite/zirconia composite is characterized by its slower kinetics and higher fuel productivity. For a cycle with a reduction temperature (Tred) of 1600 K, O2 partial pressure of 0.1 Pa and full thermodynamic conversion of the redox materials, cerium oxide achieved a maximum of 25% solar to H2 efficiency (ηSTH) for a redox ΔT of ~140 K (temperature-swing), whereas the ferrite/zirconia composite achieved 46%

ηSTH for a redox ΔT of ~250 K. The higher ηSTH for the ferrite/zirconia composite is atributed to the higher H2 production capacity of the materials as shown in Figure 2.6. Other key process parameters are shown in Table 2.1. However, the thermodynamic data for ferrite/zirconia has not been experimentally validated. Furthermore, this material suffers from slow reaction kinetics

[22], which will negatively impact the cycling time. This might lead to an increase in radiation and convection heat losses, which will affect the system efficiency. Ehrhart et al. addressed this issue by incorporating the oxidation kinetics of cerium oxide and ferrite/zirconia composite in the ηSTH model [22]. This was done by limiting the oxidation reaction cycle time to the time required to reach full conversion at ΔT = 0 K. It was found this had no impact on the fast kinetic materials like cerium oxide. However, it had a drastic impact on the slower kinetic materials like ferrite/zirconia composite, where the maximum solar to H2 efficiency was reduced to 32% for a redox ΔT of ~150 K.

Figure 2.6: H2 capacity (Δδ) for ceria and ferrite/zirconia composite at Tred = 1600 K and pO2 = 0.1 Pa. Reprinted from [22] 2.5.2. Reduction reaction processing

One of the operating challenges that has a lage impact on the ηSTF is the requirement to achieve low O2 partial pressure in the reduction reactor. Low pO2 is necessary to increase the thermodynamic driving force for the reduction reaction and drive the reaction to the right. This can be achieved by a mechanical approach using vacuum pumping and/or flowing inert gas. Lin et al. recently suggested a chemical approach to remove the generated O2 using a chemical scavenger [25].

The effect of using inert gas to reduce O2 partial pressure in the solar to fuel analysis has been explored by many groups. There are two main energy requirements associated with using inert gas: (heating inert gas to the reduction temperature and separating generated O2 from the inert gas after reduction). Many of these studies have reached conflicting conclusions when considering inert gas. Some studies suggested that using inert gas will lead to high system

efficiencies [26], while others suggested vacuum pumping will lead to higher system efficiencies than using inert gas [31]. The primary reason for these conflicting conclusions is the method of calculating the amount of inert gas required per redox cycle. Some works only considered a perfect mixing of inert gas and generated O2 [29, 31]. Other studies suggested an ideal counter- flow arrangement of the inert gas in contact with the solid metal oxides, which minimizes the amount of inert gas required. For example, the ratio of inert gas to O2 (nio) for the perfect mixing case is almost three orders of magnitude larger than the ideal counter-flow arrangement, for ceria at Tred of 1,800 K, ΔT = 0 K and a reduction pressure of 0.1 Pa. As a consequence, Bader et al. calculated 31.6% solar to H2 efficiency for ceria operating at Tred of 1773 K , εGG (gas-gas heat recuperation) of 95.5% and ΔT of 150 K with a counter-flow arrangement [26], while Ermanoski et al. calculated ~0% efficiency at similar conditions [31]. Other works compared counter-flow to parallel-flow (mixed-flow) arrangements and suggested the final flow arrangement would be an intermediate state [28, 32]. Krenzke et al. predicts a larger amount of inert gas for a mixed flow arrangement, but not as large as for perfect mixing, as shown in Figure 2.7 and lower ηSTF efficiencies compared to a counter-flow arrangement [28]. Ehrhart et al. quantified the impact of inert gas on ηSTH calculations with a counter-flow arrangement but imposed a minimum amount of inert gas to O2 ratio (nio ranged from 0 to 1,000) [20]. This is useful because the counter-flow arrangement predicts zero inert gas flow rates as shown in Figure 2.7, which is unrealistic.

Figure 2.8 shows that solar to H2 efficiency for ceria decreases as one increases the nio. Also, the optimal ΔT approaches near-isothermal operation as the amount if inert gas is increased (~28%

ηSTH at ~ 120 K ΔT). As the amount of inert gas increases further (nio > 1000), ηSTH does not change much with changing ΔT.

Figure 2.7: Inert gas to fuel (H2 or CO) ratio (RSG) for ceria reduction at Tred = 1773 K with the countercurrent flow and mixed flow arrangements. Reprinted from [28]

Figure 2.8: ηSTH for inert gas sweep with various limits on the amount of inert gas using for ceria with 1,800 K reduction temperature and 0.1 Pa reduction pressure. Reprinted from [20]

Ehrhart et al. also examined the effect of inert gas/O2 separation temperature (TSEP) on

ηSTH. They found that as one increases the separation temperature, TSEP, the solar to H2 efficiency

increases. The analysis showed 23% system efficiency for cerium oxide materials for a 1223 K

TSEP at ΔT of 110 K (temperature-swing), while 15% ηSTH for a 90 K TSEP for ΔT of 110 K [20].

Typically, a cryogenic separation plant achieves a high purity N2 inert gas at low separation temperatures [28], while an ionic transport membrane (ITM) can separate O2 at high temperatures [15]. Ehrhart et. al showed that any inert gas/O2 separation technology needs to be at least 10% efficient when comparing the energy requirements for separation to thermodynamic separation work [21]. The separation efficiency for a high temperature ITM has yet to be reported.

Some studies have suggested that using vacuum pumping in the reduction step leads to higher ηSTF than using inert gas sweeping [19, 33]. Ermanoski et al. showed a ~40% ηSTH for cerium oxide materials operating in a temperature-swing mode with ΔT of ~280 K and pO2 of 1

Pa with 10% vacuum pump efficiency (ηpump) [19]. However, others have shown that vacuum pump efficiency is pressure dependent and the lower the pressure, the less ηpump will be [18, 23].

Ehrhart et al. showed that when using current vacuum pump technology efficiencies, ηSTH is practically zero at all ΔT and a pO2 of 1 Pa and that higher reduction pressure (~10,000 Pa with

2% ηpump) is needed to have moderate efficiency (12% ηSTH at ΔT of ~350 K (TS)) [21].

Operating at higher reduction pressure leads to a lower reduction extent of the material (δRED) to produce the same amount of H2, which will require larger metal oxide flowrates.

2.5.3. Heat exchanger effectiveness

Heat recuperation has a drastic impact on the system efficiency due to the high temperatures involved. Ehrhart et al. assessed the impact of gas and solid heat recuperation by varying the gas-gas heat recuperation effectiveness (εGG) and solid-solid heat recuperation effectiveness (εSS) from 0% to 100% [20]. εGG has a lage impact on STH efficiency, especially

when the nio is ≥ 100 as shown in Figure 2.9 (a). The maximum solar to H2 efficiency occurs in the near-isothermal region, but as εGG decreases (< 50%) the STH efficiency remains relatively constant as we increase ΔT. Also, the effect of εSS on STH efficiency is shown in Figure 2.9 (b).

The solar to H2 efficiency increases with respect to ΔT (TS) as εSS increases. However, for low

εSS (< 50%) the optimal STH efficiency occurs in the near-isothermal region (ΔT < 150 K).

Ermanoski et al. limited the εGG to 80% for isothermal operation assuming that heat cannot be recovered for temperatures greater than 1273 K due to current materials limitations for metal heat exchangers [19]. However, Hathaway et al. recently demonstrated 95% of sensible gas heat recovery using a ceramic heat exchanger at ~ 1750 K, which is a very promising result for the solar thermochemical field [34].

(a)

(b)

Figure 2.9: ηSTH values for ceria with 1,800 K reduction temperature and 0.1 Pa reduction pressure. (a) Various values of gas heat recuperation (εGG), 50% solid heat recuperation (εSS) and nio ≥ 100. (b) Various values of (εSS) and 90 % εGG. Reprinted from [20]

Table 2.1: A summary of selected efficiency calculations for solar thermochemical H2O splitting pO2 Tred ΔT Heat Chemical Calculation Material (Pa) (K) (K) Method of Reduction Recuperation Basis Efficiency Citation

1600 εGG = 0.95 Ceria 0.1 K ~ 160 Inert Gas εSS = 0.5 Chemical equilibrium ~ 25% [22]

Ferrite/ 1600 εGG = 0.95 Zirconia 0.1 K ~ 250 Inert Gas εSS = 0.5 Chemical equilibrium ~ 46% [22]

1600 εGG = 0.9 Ceria 0.1 K ~ 160 Inert Gas εSS = 0.5 Kinetically limited ~ 25% [22]

Ferrite/ 1600 εGG = 0.9 Zirconia 0.1 K ~ 150 Inert Gas εSS = 0.5 Kinetically limited ~ 32% [22]

1773 Vacuum (ηpump = εGG = 0.8 Ceria 1 K ~ 280 10%) εSS = 0.75 Chemical equilibrium ~ 40% [19]

1800 Vacuum (ηpump = εGG = 0.9 Ceria 1 K all 0.01%) εSS = 0. 5 Chemical equilibrium ~ 0% [21]

1800 εGG = 0.9 Ceria 1000 K ~ 350 Vacuum (ηpump = 2%) εSS = 0. 5 Chemical equilibrium ~ 12% [21] Inert Gas (niO ≥ 100) 1800 TSEP = 1223 K εGG = 0.75 Ceria 0.1 K ~110 (ηSEP=15%) εSS = 0.5 Chemical equilibrium ~ 23% [20] Inert Gas (niO ≥ 100) 1800 TSEP = 90 K εGG = 0.75 Ceria 0.1 K ~100 (ηSEP=15%) εSS = 0.5 Chemical equilibrium ~ 15% [20]

2.6. Isothermal reactor designs

Prior to the identification of isothermal cycling, various solar reactor concepts were proposed based on temperature swing cycling. In this review, we focus on the recent proposed isothermal reactor concepts. A solar reactor that employs non-volatile redox pairs is broadly classified as a monolithic-receiver or particle-receiver reactor [1, 35]. For monolithic-reactor types, a self-supported structure is made of reactive materials where the reduction and oxidation steps are controlled by cycling the gases entering the reactor for isothermal cycling. The particle- receivers reactor type utilizes flowing reactive particles between the reduction and oxidation zones. These reactors can decouple the reduction and oxidation times since the reaction rates are expected to be different [1].

2.6.1. Monolithic-receiver reactors

The SurroundSun reactor is an insulated cavity reactor prototype with multiple reaction tubes as shown in Figure 2.10 [36]. The reaction tubes are packed with reactive particles where the reactive particles are indirectly irradiated by concentered solar energy. Reaction and oxidation reactions are controlled by the gases (H2O or inert gas) entering the tubes. However, this reactor design suffers from a major challenge being that large temperature differences can exist within the bed. This can lower the reaction rates and limit the utilization of the reactive particles.

Figure 2.10: The SurroundSun Reactor. Reprinted from [36] Another reactor design concept is the isothermal reactor shown in Figure 2.11 [34]. The reactor is a packed bed consisting of fully integrated solar receiver and heat recovery sections and housed within an insulated cavity. The solar reactor section contains 6 coaxial dense alumina tubes, where the annulus of each tube is filled with reactive particles. The inner tube is filled with alumina reticulated porous ceramic to exchange heat between the process gases. In this configuration, concentrated sunlight enters through an aperture where the reduction and oxidation reactions are controlled by the gases entering the tubes where inert gas is used to sweep the generated O2 out.

Hathaway et al. demonstrated an isothermal cycle using 5 mm porous ceria reactive particles to split CO2 with the isothermal reactor at 1750 K. CO2 and N2 inert sweep gas flowrates and cycling times were optimized to maximize the solar to CO efficiency. CO was produced for over 45 cycles and 95% of process gas sensible heat was recovered using the ceramic heat exchanger. The reported solar to CO efficiency was 0.72% [34]. This low efficiency was most likely due to the underutilization of cerium oxide where the thermodynamic CO production per

cycle (Δδ) at the reaction temperature of 1750K is 0.071 mol of CO per mol of CeO2 and the experimental production per cycle is 0.001 mol of CO per mol of CeO2.

Figure 2.11: The isothermal reactor. Reprinted from [34]

Zhu et al. suggested using a dense ceria membrane for isothermal carbon-free fuel (H2 and/or CO) production [37]. In this reactor, the outer side of the membrane is exposed to concentrated solar irradiation to reduce the active redox material under inert gas sweeping or vacuum pumping. Simultaneously, CO2 and/or H2O flows inside the membrane in the opposite direction as shown in Figure 2.12. The membrane acts as a barrier between the reduction and oxidation zones where O2 ions are transferred.

Figure 2.12: The membrane reactor. Reprinted from [37] 2.7. Summary and path forward

Pure isothermal processing is simpler, but theoretically less efficient compared to temperature-swing processing. Research needs directed towards ITS high temperature O2 separation membranes and ceramic heat exchangers for high efficiency O2-separation and steam- steam heat recuperation.

2.8. References

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16. Venstrom, L.J., et al., Efficient splitting of CO2 in an isothermal redox cycle based on ceria. Energy & Fuels, 2014. 28(4): p. 2732-2742. 17. Amar, V., J. Puszynski, and R. Shende, H2 generation from thermochemical water- splitting using yttria stabilized NiFe2O4 core-shell nanoparticles. Journal of Renewable and Sustainable Energy, 2015. 7(2): p. 023113. 18. Bulfin, B., et al., Thermodynamics of CeO2 thermochemical fuel production. Energy & Fuels, 2015. 29(2): p. 1001-1009. 19. Ermanoski, I., J. Miller, and M. Allendorf, Efficiency maximization in solar- thermochemical fuel production: challenging the concept of isothermal water splitting. Physical Chemistry Chemical Physics, 2014. 16(18): p. 8418-8427. 20. Ehrhart, B.D., et al., System efficiency for two-step metal oxide solar thermochemical hydrogen production–Part 2: Impact of gas heat recuperation and separation temperatures. International Journal of Hydrogen Energy, 2016. 41(44): p. 19894-19903. 21. Ehrhart, B.D., et al., System efficiency for two-step metal oxide solar thermochemical hydrogen production–Part 3: Various methods for achieving low oxygen partial pressures in the reduction reaction. International Journal of Hydrogen Energy, 2016. 41(44): p. 19904-19914. 22. Ehrhart, B.D., et al., System efficiency for two-step metal oxide solar thermochemical hydrogen production–Part 1: Thermodynamic model and impact of oxidation kinetics. International Journal of Hydrogen Energy, 2016. 41(44): p. 19881-19893. 23. Jarrett, C., et al., Critical limitations on the efficiency of two-step thermochemical cycles. Solar Energy, 2016. 123: p. 57-73. 24. Krenzke, P.T. and J.H. Davidson, On the efficiency of solar H2 and CO production via the thermochemical cerium oxide redox cycle: the option of inert-swept reduction. Energy & Fuels, 2015. 29(2): p. 1045-1054. 25. Lin, M. and S. Haussener, Solar fuel processing efficiency for ceria redox cycling using alternative oxygen partial pressure reduction methods. Energy, 2015. 88: p. 667-679. 26. Bader, R., et al., Thermodynamic analysis of isothermal redox cycling of ceria for solar fuel production. Energy & Fuels, 2013. 27(9): p. 5533-5544. 27. Siegel, N.P., et al., Factors affecting the efficiency of solar driven metal oxide thermochemical cycles. Industrial & Engineering Chemistry Research, 2013. 52(9): p. 3276-3286. 28. Krenzke, P.T. and J.H. Davidson, On the Efficiency of Solar H 2 and CO Production via the Thermochemical Cerium Oxide Redox Cycle: The Option of Inert-Swept Reduction. Energy & Fuels, 2015. 29. Bulfin, B., et al., Thermodynamics of CeO 2 thermochemical fuel production. Energy & Fuels, 2015.

30. Panlener, R., R. Blumenthal, and J. Garnier, A thermodynamic study of nonstoichiometric cerium dioxide. Journal of Physics and Chemistry of Solids, 1975. 36(11): p. 1213-1222. 31. Ermanoski, I., N.P. Siegel, and E.B. Stechel, A new reactor concept for efficient solar- thermochemical fuel production. Journal of Solar Energy Engineering, 2013. 135(3): p. 031002. 32. Venstrom, L.J., et al., Applicability of an equilibrium model to predict the conversion of CO2 to CO via the reduction and oxidation of a fixed bed of cerium dioxide. Energy & Fuels, 2015. 29(12): p. 8168-8177. 33. Singh, A.K., et al., Thermal reduction of iron oxide under reduced pressure and implications on thermal conversion efficiency for solar thermochemical fuel production. Industrial & Engineering Chemistry Research, 2015. 54(26): p. 6793-6803. 34. Hathaway, B.J., et al., Demonstration of a solar reactor for carbon dioxide splitting via the isothermal ceria redox cycle and practical implications. Energy & Fuels, 2016. 30(8): p. 6654-6661. 35. Agrafiotis, C., M. Roeb, and C. Sattler, A review on solar thermal syngas production via redox pair-based water/carbon dioxide splitting thermochemical cycles. Renewable and Sustainable Energy Reviews, 2015. 42: p. 254-285. 36. Martinek, J., R. Viger, and A.W. Weimer, Transient simulation of a tubular packed bed solar receiver for hydrogen generation via metal oxide thermochemical cycles. Solar Energy, 2014. 105: p. 613-631. 37. Zhu, L., Y. Lu, and S. Shen, Solar fuel production at high temperatures using ceria as a dense membrane. Energy, 2016. 104: p. 53-63.

CHAPTER 3

3. UNDERSTANDING REDUCTION KINETICS OF HERCYNTE MATERIALS FOR

SOLAR THERMOCHEMICAL H2O SPLITTING

3.1. Abstract

Solar thermochemical water splitting process (STWS) is a promising technology for producing renewable H2. This work reports the reduction kinetic study of the hercynite cycle

(FeAl2O4). The reaction kinetics has been evaluated using dynamic thermogravimetric and XRD analyses. Kinetic modeling results indicate that as-prepared hercynite materials undergoes reduction via two different reaction mechanisms. The reaction first proceeds by a nucleation and growth reaction mechanism, followed by a third-order kinetic model. XRD analyses show the occurrence of superstoichiometric oxygen in the spinel structure of FeAl2O4+δ in the second reaction mechanism, which indicates the formation of cationic vacancies. TGA and XRD analyses show that hercynite materials operates via a cation-vacancy mechanism when the materials are thermally reduced and oxidized with steam.

3.2. Introduction

Energy and environmental issues at a global level are important topics and to that extent focus has been on the generation of clean energy for some time. Hydrogen in its molecular form, as a clean energy carrier has the potential to meet at least in part the global energy needs 1.

Hydrogen is widely used as a feedstock in several energy demanding industries such as petroleum, chemicals, fertilizers and others. At present hydrogen is produced mainly from fossil fuels through methane steam reforming. Because of the nonrenewable nature and the large amounts of CO2 associated with the steam reforming/water gas shift process research, for a while now, focus has shifted to the development of new methods to produce hydrogen from water.

Solar thermochemical water-splitting (STWS) is a promising method for producing H2 which uses the abundant solar energy as an energy source 2-5. Solar energy is concentrated using mirrors, which is then focused on a reactor to drive a two-step redox cycle. In the first step a metal oxide is thermally reduced under low O2 partial pressure to generate O2. Then, in the second step the reduced metal oxide is oxidized again using water as the oxidizing agent with the consequent generation of H2. Two-step water splitting reactions can be classified by their reaction mechanisms: volatile stoichiometric chemistries, nonvolatile stoichiometric chemistries, or oxygen vacancy chemistries 3. The volatile stoichiometric chemistries produce gaseous

6 products (e.g., ZnO(s) → Zn(g) + ½ O2) , where the nonvolatile stoichiometric chemistries

7 produce solid products with an altered crystal structure (e.g., Fe3O4 → 3FeO + ½ O2) . In oxygen vacancy chemistries, oxygen is released by the formation of oxygen vacancies in the

8 metal oxide lattice (e.g., CeO2 → CeO2-δ + δ/2 O2) , where δ is the extent of non-stoichiometry.

Currently, the focus of recent research has been on oxygen vacancy chemistries due to its stability over many water splitting cycles.

Currently, there are three identified redox materials under investigation for STWS cycles: the ceria, perovskite cycles and hercynite cycle. It has been shown that both ceria and perovskites cycles operate by the oxygen vacancy mechanism 3. The hercynite materials is promising because of its stability 9,10 and high hydrogen production capacity compared to cerium oxide 11. The kinetics and reaction mechanism of hercynite redox cycles, which are expected to play a critical role in reactor design, are poorly understood. The hercynite redox cycle was originally thought to operate through a stoichiometric mechanism as shown in equation (3.1) 9.

퐹푒2푂3 + 2 퐴푙2푂3 → 2 퐹푒퐴푙2푂4 + 0.5 푂2 (3.1)

However, it has been shown later through DFT calculations that hercynite and cobalt-doped hercynite materials operate through an oxygen vacancy mechanism 12.

In this work, reduction kinetics of the hercynite materials have been analyzed for the first time by TGA and X-ray diffraction (XRD) technique. Solid-state kinetics theory is used to describe the first step of the hercynite redox cycle for solar thermochemical water splitting. The findings from this study will elucidate the reaction mechanism for the hercynite cycle.

3.3. Experimental methods

3.3.1. Materials preparation

Hercynite particles were fabricated via dynamic mixing at Coorstek, Inc. in an Eirich

Intensive Mixer Type RV02E. Each batch of particles contained approximately 2240g Al2O3 powder (Sigma-Aldrich aluminum oxide powder, ≤ 10μm avg. part. size, 99.5% trace metal basis) and 1760g Fe2O3 powder (Sigma-Aldrich iron(III) oxide powder, <5μm, ≥99%), along with a binder containing 133g corn starch, 267g maltodextrin, and 300g water. Dry ingredients were mixed for 1:30 minutes using a rotor speed of 7.5 m/s and a pan speed of 30Hz. The liquid binder was then added slowly over the course of 2:30 minutes followed by a 1:00 minute hold at the same mixing speeds. This was followed by a granulation step where the rotor speed was increased to 25 m/s and the pan speed remained at 30Hz. The particles were hardened by placing them over a hot vent for approximately 1 hour. The particles were dried in an oven at 150oC for 4 hours, pyrolyzed, and calcined in air at 850oC for 24 hours.

3.3.2. Kinetic studies

Hercynite reduction kinetics are performed using thermogravimetric analyses (TGA).

Samples of ~15 mg of hercynite materials are introduced in a plate shaped alumina crucible placed in a vertical sample holder in the TGA. Low amount of materials is used to avoid mass

transfer limitations 13. Reduction kinetics are analyzed using dynamic experiments at multiple heating rates (β = 5.0, 7.5, 10.0 and 10 °C min) from 900°C to 1500°C under argon atmosphere.

Gas flow rate were optimized to avoid gas mass transfer limitations by increasing the flow rates until the weight loss upon reduction is not changing.

The gas-solid kinetic equation under isothermal condition is described by an Arrhenius- type law 14:

퐸 푑훼 − 푎 (3.2) = 퐴푒 푅푇푓(훼) 푑푡 where α is the reaction conversion, A is the pre-exponential factor, Ea is the activation energy, R is the universal gas constant, T is temperature and f(α) is the differential form of the reaction model. Reaction models are mathematical equations derived based on mechanistic assumptions to give an insight on a reaction mechanism. Most common reaction models are shown in

Table 3.1 15. The oxidation kinetics is studied non-isothermally to determine the kinetic behavior of the materials over the temperature range (100 – 1000°C). For non-isothermal experiments with constant heating rates ( = dT/dt), the kinetic equation becomes

퐸 푑훼 퐴 − 푎 (3.3) = 푒 푅푇푓(훼) 푑푇 훽

The integral form of the kinetic equation is shown in Equation (3.4).

푇 −퐸 푑훼 퐴 ( 푎) (3.4) 푔(훼) = = ∫ 푒 푅푇 푑푇 푓(훼) 훽 0 where g() is the integral form of the reaction model.

Table 3.1 Solid-state reaction models in differential from. Kinetic model Kinetic mechanism 푓(훼) P2 Power law 2훼(1/2) P3 Power law 3훼(2/3) P4 Power law 4훼(3/4)

An Avrami-Erofeev 푛(1 − 훼)[−ln (1 − 훼)](n−1/n) R2 Contracting area 2(1 − 훼)1/2 R3 Contracting volume 3(1 − 훼)2/3 D1 1-D diffusion 1/(2훼) D2 2-D diffusion [−ln (1 − 훼)]−1 D3 3-D diffusion-Jander 3/2(1 − 훼)2/3[1 − (1 − 훼)1/3]−1 D4 Ginstling-Brounshtein 3/2[(1 − 훼)−1/3 − 1] 푛 Fn Reaction order of n (1 − 훼)

In literature, two main calculation methods for determining reaction kinetic parameters exist 16. One is the model fitting method where the kinetic triplet (A, Ea, f(α)) is determined.

Two issues with this method is that it does not show if the reaction has more than one rate- limiting step, and the kinetic parameters can depend strongly on the reaction model chosen.

Therefore, another method has been developed, the isoconversional method. This method calculates the activation energy as a function of conversion independent of a model. This determines if more than one rate-limiting step exists for the reaction if the activation energy changes significantly as the reaction progresses 16. From there the data can be fit to as many models as needed depending on number of rate-limiting steps.

3.3.3. Materials characterization

Crystal structure of the hercynite materials after calcining is determined using a Bruker

D2 Phaser X-Ray Diffraction Desktop System with Cu Kα radiation (λ = 1.5418 Å). Evaluation of hercynite reduction reaction mechanism is analyzed using XRD. The selection of the best- fitted reaction model is supported by XRD analyzes. XRD analyses are performed on materials reduced at different reduction temperatures (1100°C, 1200°C, 1300°C, 1400°C and 1500°C).

3.4. Results and discussions

3.4.1. Experimental TGA results

Four TGA runs at different heating rates were carried out to extract kinetic data of the hercynite reduction reaction under an argon atmosphere. Figure 3.1 depicts the mass loss versus time plots of the hercynite reduction reaction. From these data it was possible to determine the activation energies as a function of conversion using the isoconversional analysis. Reaction conversion, α, is calculated based on the thermogravimetric data as shown in Equation (3.5) 16.

푚 − 푚 훼 = 0 푇 (3.5) 푚0 − 푚푓

where m0 is the initial weight of the sample, mT is weight at temperature T, mf is the final weight. The final mass is calculated according to the stoichiometry reaction of hercynite formation shown in equation (3.1). Theoretical mass loss for the total conversion of hercynite formation according to the stoichiometry of the reaction is 4.40%. Interestingly, none of the four heating rates experiment reached the theoretical mass loss for full reaction conversion to form

FeAl2O4. Another finding from the mass loss versus time graph of the hercynite reduction reaction is that there are two distinct slopes, which indicates two different reaction mechanisms.

Figure 3.1 Mass loss versus time plots for hercynite reduction, carried out heating up to 1500 °C under an argon atmosphere 3.4.2. Kinetic modeling

3.4.2.1. Isoconversional analysis

Figure 3.2 depicts the conversion versus temperature plots of the hercynite reduction reaction. Isoconversional analysis allows for the calculation of activation energy as a function of conversion without prior knowledge of a physical model, f(α). This is done by taking the natural logarithm of the reaction rate shown in Equation (3.4). Since the reaction rate equation has an integral that does not have an analytical solution, several approximations have been proposed which give rise to a linear equation.

Figure 3.2: conversion versus temperature plots for hercynite reduction, carried out at multiple heating rates Two accurate approximations, Kissinger-Akahira-Sunose (KAS) and Starink, were applied to calculate the activation energy as shown in Equations (3.6) and (3.7), respectively .

훽푖 퐸푎 (3.6) ln ( 2 ) = 퐶표푛푠푡 − 푇훼,푖 푅푇훼 훽푖 퐸푎 (3.7) ln ( 1.92) = 퐶표푛푠푡 − 1.0008 푇훼,푖 푅푇훼

The activation energy at each given α is determined from the slope of the two equations. All plots for each given α resulted in a linear relationship with a high correlation coefficient (> 98%).

Figure 3.3 provides the results of the isoconversional computations of hercynite reduction reaction at incremental conversion values of 5%.

Figure 3.3: Ea versus α calculated using KAS and Starink isoconversional methods

Isoconversional kinetic analysis using the KAS and Starink methods shows two distinct regions where the calculated activation energies differ in value. The first region is from 5% to

35% conversion where the average activation energy is 483 ± 9 kJ mol-1. The second region is from 30% to 80% where the activation energy is 252 ± 15 kJ mol-1.

3.4.2.2. Model fitting methods

The differential equation shown in equation (3.3) can be solved by selecting a specific kinetic model for the function f(α) from Table 3.1. The estimation of the kinetic parameters for each model can be carried out by simulations fitting the equation to the four-experimental data using a nonlinear regression analysis.

Direct model fitting of the experimental data to equation (3.4) was carried out by minimizing the sum of quadratic residuals (SQR). Table 3.2 and Figure 3.4 show the results of the four models that has the lowest SQR. However, none of these models gave a satisfactory fit

for the hercynite reduction reaction. Furthermore, none of the calculated activation energies for the different models are close the calculated activation energy using the isoconversional method.

Table 3.2. Kinetic parameters calculated for the best individual fitting of the experimental at β = 10.0°C/min. log (A) Ea SQR A0.5 7.8 276 746 F3 7.6 254 399 D3 6.7 278 847 P2 2.3 115 2712

Figure 3.4. Comparison between the experimental TGA results at β = 5.0°C/min and calculated data using AE0.5, F3, D3 and P2 fitting models

Based on the finding from the isoconversional analysis that there are two distinct activation energies, direct model fitting of the experimental data is applied to two different regions (α = 0 – 35% and α > 35%) using a multivariate nonlinear regression analysis to fit

simultaneously the data for the four heating rate experiments. Table 3.3 summarizes the results obtained for the best fitting model along with the fitted kinetic parameters and SQR.

Table 3.3. Kinetic parameters calculated for the best individual fitting of the experimental data for two different regions.

α = 0 - 35% α > 35% β (°C/min) AE1 F3 log(A) Ea RSQ log(A) Ea RSQ 5.0 13 1.3 7.5 18 0.4 16.4 ± 0.6 469 ± 6 7.1 ± 0.4 259 ± 3 10.0 2 0.7 12.5 11 0.6

Figure 3.5 shows that the first reaction is well described by an Avrami-Erofeev, AE1, while the second reaction is well described by third reaction order model, F3. Furthermore, the activation energies found for both models are close to the activation energies calculated using the isoconversional methods.

Figure 3.5: TGA experimental data and predictions with Avrami-Erofeev, AE0.5, model (α = 0 – 35%) and reaction order, F3, model (α > 35%) at different heating rates a) 5.0, b) 7.5, c) 10.0 and d) 12.5°C/min

In the first kinetic region, the conversion curve appears to have a sigmoidal shape, where an Avrami-Efrofeev model best fit the experimental data with an Avrami exponent n of 1. This value describes a linear diffusion-controlled growth and instant nucleation at the beginning of the phase transformation 17. The nucleation and growth model described by Avrami-Efrofeev models proceeds by nucleation and subsequent nuclei growth 18. Figure 3.7 shows the possible steps during the reduction of hercynite materials following the nucleation and nuclei growth model.

An induction period precedes nucleation to activate the solid phase to form nuclei. The active site happens at the interface between the Fe2O3 and Al2O3 grains to from the new FeAl2O4 phase.

This is followed by an acceleratory step (growth of nuclei). Then a final deceleration step which indicates the completion of reaction.

Figure 3.6. Schematic description of Avrami-Efrofeev family models

In the second kinetic region, the reaction rate is limited by a third-order model, F3, in which the rate is proportional to the remaining fraction of reactant 19. The reaction mechanism will be discussed in the next section.

3.4.2.3. Crystallographic transformation during reduction reaction

To get further insight about the reaction mechanism of hercynite reduction, XRD analyses were performed on calcined sample, 11%, 30%, 46%, 71% and 80% reduced samples.

This technique is helpful to understand the reaction mechanism by studying the phase transition that takes place during hercynite reduction reaction. Figure 3.7 displays the XRD spectra recorded for reduced hercynite samples at different reaction conversions.

XRD spectra of calcined hercynite materials indicate that aluminium oxide and iron oxide did not form the hercynite phase when calcined at 850°C (0% conversion). The lack of hercynite spinel formation has been observed previously at 1000°C and 1 atm O2 and it was attributed to

20 hematite phase (Fe2O3) being more thermodynamically stable . The formation of spinel phase starts to form at 11% conversion sample with one peak attributed to FeAl2O4 appears at 2θ of ~

31° as shown in Figure 3.7. With the progress of reduction reaction, evolution of hercynite spinel phase and concomitant decrease of Fe2O3 peak intensity are observed. Fe2O3 peaks completely disappears from the XRD patterns at 46% conversion sample. The formation of the spinel phase and disappearance of the hematite phase explains the reduction reaction in the first kinetic region is described by a nucleation and growth mechanism.

Figure 3.7: X-ray diffraction spectra for calcined and reduced hercynite materials

All peaks associated with hercynite spinel phase appears at the 46% conversion sample.

The formation of spinel phase before the complete conversion of the stoichiometric reaction shown in equation (3.1) indicates the formation of superstoichiometric oxygen in the structure of

FeAl2O4+δ with δ>0. Nonstoichiometry in spinel structure metal oxides has been observed in previous studies 21-23.

The spinel peaks shift to higher 2θ position as the material undergoes further reduction as shown in Figure 3.7. The shift to a higher 2θ position indicates a lattice contraction, which is counterintuitive since one may expect lattice expansion due to reduction of Fe3+ to Fe2+. The lattice contraction in the spinel phase can be attributed to the presence of cation vacancies in the superstoichiometric spinel (FeAl2O4+δ). The value of δ decreases as the hercynite further reduces which will cause decease in the number of cation vacancies.

Based on the findings from the isoconversional kinetic and XRD analyses, the hercynite reduction reaction shown in equation (3.1) will split into two reactions shown in equation (3.8)

(formation of the spinel phase) and equation (3.9) (with no phase change).

(1 − 2훿) (3.8) 퐹푒 푂 + 2 퐴푙 푂 → 2 퐹푒퐴푙 푂 + 푂 2 3 2 3 2 4+훿 2 2 (훿 − 훿 ) (3.9) 퐹푒퐴푙 푂 → 퐹푒퐴푙 푂 + 푟푒푑 표푥 푂 2 4+훿표푥 2 4훿표푥 2 2

From the model-fitting method, the first reaction is well described by a nucleation and growth mechanism, where the second reaction is well described by a third-reaction order model, where the reaction rate is proportional to the remaining fraction of the cation vacancies.

3.4.3. Reduction reaction mechanism with H2O splitting

To study the hercynite redox cycle reaction mechanism for solar H2O splitting, hercynite materials were thermally reduced to 1500°C and oxidized with H2O at 1350°C in a furnace reactor. The materials were then cooled down to 1000°C under steam flow to prevent reduction.

The materials were further cooled down to room temperature under argon flow. The oxidized materials were introduced into the TGA to investigate the reduction mechanism after H2O splitting. The materials were reduced to 1500°C under argon flow with 5°C/min and 10°C/min ramping rates. Figure 3.8 shows that the hercynite materials oxidized with H2O reduced with the

second reaction mechanism, where the reaction rate is controlled by the concentration of cation vacancies.

Figure 3.8: Mass loss versus temperature plots for reduction of calcined and oxidized (with H2O) hercynite materials at different heating rates a) 5°C/min, b) 10°C/min The XRD spectra for the reduced and oxidized hercynite materials shown in Figure 3.9 that the hercynite redox cycle operates via a cation vacancy mechanism where no phase change.

Figure 3.9: X-ray diffraction spectra for reduced and oxidized (H2O) hercynite materials

3.5. Conclusions

The reduction of hercynite materials in argon gas has been studied in the TGA.

Isoconversional and XRD analyses show the reaction has two different reaction mechanisms.

The reaction first follows a nucleation and growth model where the rate is described by an

Avrami-Erofeev model with an exponent of 1. The reaction mechanism changes to a third-order reaction model. Activation energies determined by model fitting methods were close the activation energies calculated by the isoconversional methods.

The reduced hercynite materials did not revert back to the starting hematite phase (Fe2O3) and corundum phase (Al2O3) when oxidized by steam. Thus, the oxidized hercynite materials by steam undergoes a single reaction mechanism described by a third-order reaction model. The

XRD spectra for the reduced and oxidized hercynite materials show that the hercynite redox cycle operates via a cation vacancy mechanism with no phase change rather than the previously reported displacement and O-vacancies mechanisms. Operating the redox cycle with no phase change contribute to the robustness of hercynite as a redox active material for spitting water.

3.6. References

1. Idriss H. Ethanol reactions over the surfaces of noble metal/cerium oxide catalysts. Platinum metals review. 2004;48(3):105-115. 2. Charvin P, Abanades S, Flamant G, Lemort F. Two-step water splitting thermochemical cycle based on iron oxide redox pair for solar hydrogen production. Energy. 2007;32(7):1124-1133. 3. Muhich CL, Ehrhart BD, Al‐Shankiti I, Ward BJ, Musgrave CB, Weimer AW. A review and perspective of efficient hydrogen generation via solar thermal water splitting. Wiley Interdisciplinary Reviews: Energy and Environment. 2015. 4. Coelho B, Oliveira A, Mendes A. Concentrated solar power for renewable electricity and hydrogen production from water—a review. Energy & Environmental Science. 2010;3(10):1398-1405.

5. Al-Shankiti I, Ehrhart BD, Weimer AW. Isothermal redox for H2O and CO2 splitting–A review and perspective. Solar Energy. 2017;156:21-29. 6. Steinfeld A. Solar hydrogen production via a two-step water-splitting thermochemical cycle based on Zn/ZnO redox reactions. International Journal of Hydrogen Energy. 2002;27(6):611-619. 7. Nakamura T. Hydrogen production from water utilizing solar heat at high temperatures. Solar energy. 1977;19(5):467-475. 8. Kaneko H, Miura T, Ishihara H, et al. Reactive ceramics of CeO2–MOx (M= Mn, Fe, Ni, Cu) for H2 generation by two-step water splitting using concentrated solar thermal energy. Energy. 2007;32(5):656-663. 9. Scheffe JR, Li J, Weimer AW. A spinel ferrite/hercynite water-splitting redox cycle. International Journal of Hydrogen Energy. 2010;35(8):3333-3340. 10. Lichty P, Liang X, Muhich C, Evanko B, Bingham C, Weimer AW. Atomic layer deposited thin film metal oxides for fuel production in a solar cavity reactor. international journal of hydrogen energy. 2012;37(22):16888-16894. 11. Muhich CL, Evanko BW, Weston KC, et al. Efficient generation of H2 by splitting water with an isothermal redox cycle. Science. 2013;341(6145):540-542. 12. Muhich CL, Ehrhart BD, Witte VA, et al. Predicting the solar thermochemical water splitting ability and reaction mechanism of metal oxides: a case study of the hercynite family of water splitting cycles. Energy & Environmental Science. 2015;8(12):3687- 3699. 13. Carrillo AJ, Serrano DP, Pizarro P, Coronado JM. Understanding redox kinetics of iron- doped manganese oxides for high temperature thermochemical energy storage. The Journal of Physical Chemistry C. 2016;120(49):27800-27812. 14. Khawam A, Flanagan DR. Basics and applications of solid‐state kinetics: A pharmaceutical perspective. Journal of pharmaceutical sciences. 2006;95(3):472-498. 15. Khawam A, Flanagan DR. Solid-state kinetic models: basics and mathematical fundamentals. The journal of physical chemistry B. 2006;110(35):17315-17328. 16. Vyazovkin S, Burnham AK, Criado JM, Pérez-Maqueda LA, Popescu C, Sbirrazzuoli N. ICTAC Kinetics Committee recommendations for performing kinetic computations on thermal analysis data. Thermochimica Acta. 2011;520(1):1-19. 17. Cumbrera F, Sanchez-Bajo F. The use of the JMAYK kinetic equation for the analysis of solid-state reactions: critical considerations and recent interpretations. Thermochimica acta. 1995;266:315-330. 18. Hossain MM, de Lasa HI. Reduction and oxidation kinetics of Co–Ni/Al2O3 oxygen carrier involved in a chemical-looping combustion cycles. Chemical Engineering Science. 2010;65(1):98-106.

19. Botas J, Marugán J, Molina R, Herradón C. Kinetic modelling of the first step of Mn2O3/MnO thermochemical cycle for solar hydrogen production. international journal of hydrogen energy. 2012;37(24):18661-18671. 20. Bolt P, Habraken FH, Geus J. Formation of nickel, cobalt, copper, and iron aluminates fromα-andγ-alumina-supported oxides: a comparative study. Journal of Solid State Chemistry. 1998;135(1):59-69. 21. Bulavchenko O, Venediktova O, Afonasenko T, et al. Nonstoichiometric oxygen in Mn– Ga–O spinels: reduction features of the oxides and their catalytic activity. RSC Advances. 2018;8(21):11598-11607. 22. Gillot B, Laarj M, Kacim S. Reactivity towards oxygen and cation distribution of manganese iron spinel Mn 3-x Fe x O 4 (0≤ x≤ 3) fine powders studied by thermogravimetry and IR spectroscopy. Journal of Materials Chemistry. 1997;7(5):827- 831. 23. Sheldon RI, Hartmann T, Sickafus KE, et al. Cation disorder and vacancy distribution in nonstoichiometric magnesium aluminate spinel, MgO· xAl2O3. Journal of the American Ceramic Society. 1999;82(12):3293-3298.

CHAPTER 4

4. DESIGN OF MANGANESE OXIDE-BASED PARTICLES FOR HIGH-TEMPERATURE

THERMOCHEMICAL ENERGY STORAGE

4.1. Abstract

High-temperature thermochemical energy storage shows promise in aiding concentrating solar power plants in meeting variable, grid-scale electricity demand. In this work, manganese oxide-based mixed metal oxide particles have been designed and tested for thermochemical energy storage. Particles are designed for high energy storage capacity, flowability, and physical and chemical stability. We evaluate the effects of Al2O3, Fe2O3, and ZrO2 in Mn2O3-based spray- dried particles in a TGA between 650°C and 1,200°C over six consecutive redox cycles. Results are compared with thermodynamic predictions from 400–1,400°C under oxidizing and reducing atmospheres. A mixture of 2:1 Fe2O3:Mn2O3 formed iron manganese oxide spinel (MnFe2O4) on calcination, and demonstrated the highest thermochemical activity. Conversely, zirconia was an inert support that does not react with manganese oxide. The oxidation reaction kinetics of

MnFe2O4 has been evaluated using solid-state kinetics theory and XRD analysis. A kinetics study indicates that the reaction proceeds by two different reaction mechanisms. The reaction first proceeds by a diffusion-controlled reaction mechanism with no phase change, followed by a nucleation-growth reaction mechanism.

4.2. Introduction

High-temperature thermochemical energy storage is a promising approach for efficient and cost-effective storage of concentrated solar energy for dispatchable solar-thermal power generation. Solid metal oxide materials are considered as high-temperature thermochemical energy storage media as they often reduce at the high temperatures reachable with point-focusing

solar concentrating systems and have the potential to reach high energy storage densities 1-4.

Manganese oxide is of particular interest as it is inexpensive, non-corrosive, and relatively hazard-free. It reversibly reduces from Mn2O3 to MnO in the temperature range of 500 to

1,500°C in an oxygen-lean environment. Particles can then be redox cycled in a thermochemical storage system involving two fluidized-bed reactors, one for solar-driven high-temperature endothermic reduction to “charge” the particles and one for non-solar lower-temperature exothermic oxidation to “discharge” the particles. The goal is to develop easily flowable particles that exhibit high storage capacity, physical robustness, and chemical activity over thousands of redox cycles.

Manganese-containing oxides have shown promise as redox materials for solar thermochemical water splitting 5-7 and chemical looping combustion 8,9. A cycle utilizing sodium hydroxide with pure manganese oxide over three or more reactions has been studied 10-15, as pure manganese oxide alone is not able to split water 16. In these cycles, various oxidation states of manganese oxide have been matched to temperatures and co-reactants to utilize the various oxidation states of manganese oxide. Manganese oxide has also been studied for thermochemical energy storage. Wong et al. studied the thermodynamics of this material for thermochemical energy storage 17. Carrillo et al. tested manganese oxide over many cycles and found it to be highly chemically stable and very promising as a thermochemical storage material 18,19.

A stable form of manganese oxide at room temperature is Mn2O3. As Mn2O3 is heated to higher temperatures, it undergoes several reduction steps, shown in Equation (4.1).

Mn2O3 ↔ α − Mn3O4 ↔ β − Mn3O4 ↔ MnO (4.1)

As hot MnO is cooled down to room temperature, it reoxidizes via several oxidation steps back to Mn2O3. The temperatures at which these transitions occur depend on the gas environment in

which the reaction is conducted. Indeed, it is possible to reduce the material further, past MnO to

Mn (pure metal), or to oxidize the material past Mn2O3 to MnO2. However, the use of the pure metal presents operational challenges, and MnO2 is typically not observed upon reoxidation, as a very high oxygen partial pressure is required 20.

Spray drying is a commonly used method of making high-performance, fluidizable particles for chemical looping combustion applications 21,22 which have been shown to withstand long exposure for high temperature cycling 23. The morphology of spray dried particles impacts flowability and friability 24. Spherical particles tend to require higher gas velocities for fluidization, but tend to give higher quality fluid beds with less agglomeration 25. Furthermore, spherical particles are likely to have longer useful lifetimes in a physically and thermally stressful environment than particles of other shapes 26. Colloidal metal oxide dispersions are often used in the manufacture of spray-dried particles to create better particle cohesion during the spraying process and to improve the particle robustness under high-temperature cycling conditions by acting as a structural support for the active material in the particle 27. Some metal oxide dopants (including Fe2O3, ZrO2, CuO, ZnO, and TiO2) can increase the typically slow

20 kinetics of the reoxidation step Mn3O4 → Mn2O3 . On the other hand, structural supports are typically chemically inactive. Hence, adding an inactive second metal oxide to the particles reduces their mass-specific oxygen exchange capacity and energy storage density.

A number of secondary oxides have been examined for use in thermochemical energy storage with manganese oxide 28,29. Some of these improve re-oxidation performance 17 while others rely on a multi-doped manganese perovskite 30-32. Carrillo et al. found that while mixed

Co/Mn oxides performed worse than the corresponding pure oxides 18, Fe-doping of the Mn oxide improved energy storage density and reaction stability 33. Azimi et al. showed active

particles with a 2:1 Fe:Mn molar ratio in a high-temperature redox cycle optimized the activity of particles and also their retention of fluidizable, spherical morphology over multiple cycles.

Particles made with lower Fe:Mn ratios did not release oxygen when temperature cycled, and particles made with higher Fe:Mn ratios experienced sintering and defluidization at the temperatures tested 34. However, it was not clear why this behavior occurred. Later, Azimi et al. examined the addition of aluminum oxide to Fe/Mn materials and found a trade-off between chemical reactivity and physical robustness 9.

In this work, we evaluate the effect of three secondary metal oxides (Al2O3, ZrO2, and

Fe2O3) on the redox behavior and sintering temperatures of manganese-oxide-based materials.

The secondary oxides were chosen to increase structural robustness (Al2O3, ZrO2) or chemical reactivity (ZrO2, Fe2O3). Colloidal suspensions of the secondary metal oxides are combined with

Mn2O3 nanopowder to form a precursor solution used to manufacture spray-dried particles.

Elemental analysis revealed that the Mn2O3 nanopowder used to make the spray-dried particles contains sodium (~0.5 wt%). Therefore, another preparation method, intensive mixing, is used to prepare iron manganese oxide materials to study the effect of sodium contamination on redox cycling. Particles are tested in a thermogravimetric analyzer (TGA) over six consecutive redox cycles with an oxidation temperature of 650°C and reduction temperatures of 1,100°C and

1,200°C, to evaluate the impact of the different secondary metal oxides on chemical activity and robustness of the particles. The particles are characterized with respect to their shape, crystal structure, and specific surface area, using scanning electron microscopy (SEM), X-ray diffraction

(XRD), and Brunauer–Emmett–Teller (BET) surface area. This characterization helps to explain various performance trends and trade-offs for future development of these particles.

In this work, we also study the oxidation kinetics of the iron manganese oxide materials in air using TGA and XRD. XRD analyses of the materials provide an insight on the crystal transformation of the materials during the oxidation reaction.

4.3. Methods

4.3.1. Particle formation

Spray-dried manganese oxide and mixed metal oxide particles are synthesized using a

Büchi B-290 Mini Spray Dryer. Four candidate materials are evaluated in this study, and are summarized in Table 4.1. A slurry of Mn2O3 nanopowder (US Research Nanomaterials Mn2O3

Nanopowder), DI water, and a colloidal secondary metal oxide (Nyacol ZrO2(AC) Acetate stabilized colloidal zirconia, Nyacol AL20DW Colloidal alumina, or Aldrich Iron (III) oxide dispersion) is prepared and mixed on a stir plate for 20 minutes at 400 rpm. 1M NaOH or 1M

HCl are added dropwise to the slurry to affect the coagulation of particles, which contributes to a more stable droplet formation during spray-drying 35. The Fe67 slurry was the most affected by pH tuning, becoming viscous around pH 7–8; increased viscosity is indicative of more stable droplet formation. None of the other slurries appeared to be affected by pH tuning, with no visible coagulation of the slurry over a pH range of 4–11. Using pH alone to control the dispersion of a mixed-oxide suspension has been previously identified as difficult 36, but additional effort is required to determine if such control is possible for these solutions, such as zeta potential measurements. Prepared slurries are 20-30 wt% solids, and the powders and colloidal dispersions used all have particle diameters < 100 nm. The slurry is fed into the nozzle of the spray dryer via a peristaltic pump where it is nebulized with compressed air to form droplets. The liquid droplets are entrained in a flow of hot air (~200 C) in the drying chamber.

Particles form as the droplets dry and are then collected and separated from ultra-fines using a cyclone.

Samples of mixed manganese oxide and iron oxide used in this study were prepared by means of a build-up granulation, which was performed at CoorsTek, Inc. In this process, technical grade powders of Fe2O3 (Sigma Aldrich) and Mn3O4 (US Research Nanomaterials) were mixed with an Fe:Mn molar ratio of 2:1, along with a binder containing corn starch, maltodextrin, and deionized water. An Eirich Intensive Mixer Type RV02E was used for the granulation of the Fe67 materials. Dry ingredients were mixed for 1.5 hours using a rotor speed of 7.5 m/s and a pan speed of 30Hz. The liquid binder was then added slowly over the course of

2.5 hours followed by one-minute hold at the same mixing speeds. This was followed by a granulation step where the rotor speed was increased to 25 m/s and the pan speed remained at

30Hz. The particles were hardened by placing them over a hot vent for approximately 1 hour.

The particles were dried in an oven at 150°C for 4 hours, then pyrolyzed in N2 at 650°C for 2 hours.

Table 4.1 Overview of composition and sample ID for candidate materials. Description Sample ID

Mn2O3 spray dried with no secondary metal oxide NS

Mn2O3 spray dried with 30wt% Al2O3 Al30

Mn2O3 spray dried with 30wt% ZrO2 Zr30

Mn2O3 spray dried with 67wt% Fe2O3 Fe67_SD

Mn2O3 with 67wt% Fe2O3 (Intensive Mixing) Fe67_IM

All particles are calcined in a box furnace under ambient atmosphere at 1,200C for 8 hours. This was done to form the thermodynamically favorable mixed metal oxide phases, and to sinter the particles prior to TGA analysis.

4.3.2. Thermodynamic predictions

Thermodynamic equilibrium calculations are performed to predict the chemical and phase composition of manganese oxide-based materials as a function of secondary metal oxide, temperature, and gas environment. These calculations indicate the temperatures at which the reaction steps shown in Equation (4.1) occur, and the temperature ranges in which manganese oxide and the secondary metal oxide form mixed metal oxide phases. In addition, the results yield the upper temperature limit imposed by the formation of a slag phase (liquid solution phase), which results in sintering of the particles. The parameters used in the calculations are summarized in Table 4.2.

Table 4.2. Parameters used in the thermodynamic equilibrium calculations of manganese oxide- based mixed metal oxides. Parameter Value and Unit Pressure 1 atm Temperature 400-1,400°C

Secondary metal oxides ZrO2, Al2O3, Fe2O3

Initial solid material 1 mol of mixed metal oxide (Mn2O3 + secondary)

Initial gas compositions Inert gas: 100 mol N2; Air: 79 mol N2, 21 mol O2

Calculations are performed using the FactSage Gibbs free energy minimization software package 37. This software uses a thermodynamic database of enthalpy and entropy values, which are combined to calculate the Gibbs free energy for a variety of materials at the specific conditions of interest. The total Gibbs free energy of the system is then calculated subject to mass constraints, and the amounts of various possible materials are varied to minimize the free energy 38. All possible gas, liquid, and solid compounds from the FactPS and FToxide databases

were considered as possible products within FactSage. Furthermore, all possible solid solutions in the FToxid database are included, the inclusion of which has been shown to have a dramatic effect on equilibrium results when ferrites 39. Maximum theoretical mass changes during reduction and oxidation were calculated for the candidate materials using reaction stoichiometry.

4.3.3. Particle characterization

Particles are characterized before and after calcining. Particles are imaged in a JEOL

JSM-6480LV Scanning Electron Microscope using a 10 kV accelerating voltage. The BET surface area is obtained using a Micrometrics Gemini V Surface Area and Pore Size Analyzer, and crystal structure of the spray-dried materials after calcining is determined using a Bruker D2

Phaser X-Ray Diffraction Desktop System with Cu Kα radiation (λ = 1.5418 Å). Particle composition was determined by inductively coupled plasma optical electron spectroscopy (ICP-

OES) using an ARL 3410+ inductively coupled optical emission spectrometer. Samples were digested prior to ICP-OES analysis using a mixture of hydrochloric, hydrofluoric, and nitric acid at 95°C for two hours, after which boric acid was added and held for 15 minutes, samples were cooled, diluted, and analyzed.

4.3.4. Thermogravimetric analysis

Thermogravimetric analyses are performed with a Netzsch STA 449 F1 Jupiter. Samples of ~20 mg calcined metal oxide particles are placed in an alumina-lined platinum crucible. Prior to redox cycling, samples are heated to 105°C for 30 minutes to remove any adsorbed water.

After the drying step, samples are redox cycled six times under air flow. Each candidate material was cycled at two different reduction temperatures (1,100, or 1,200°C) and an oxidation temperature of 650°C. One redox cycle consists of a 10°C/min ramp to the reduction

temperature, a 15 minute hold at the reduction temperature, and a 10°C/min ramp down to the oxidation temperature followed by a 15 minute hold at the oxidation temperature.

4.3.5. Oxidation kinetic studies

Oxidation kinetics study of the best performing redox materials are completed using the

TGA. The redox materials were first reduced in a high temperature furnace under N2 atmosphere at 1200°C. Then, the reduced materials were cooled down to room temperature under N2 atmosphere to prevent oxidation. Samples of ~15 mg of reduced material are introduced in a plate shaped alumina crucible placed in a vertical sample holder in the TGA. Oxidation kinetics are analyzed using dynamic experiments at multiple heating rates (β = 2.5, 5.0, 7.5 and 10 °C min) from 50°C to 1000°C under an air atmosphere. Gas flow rate were optimized to avoid gas mass transfer limitations by increasing the flow rates until the weight increase upon oxidation is not changing.

The gas-solid kinetic equation under isothermal condition is described by an Arrhenius- type law 40:

퐸 푑훼 − 푎 (4.2) = 퐴푒 푅푇푓(훼) 푑푡 where α is the reaction conversion, A is the pre-exponential factor, Ea is the activation energy, R is the universal gas constant, T is temperature and f(α) is the differential form of the reaction model. Reaction models are mathematical equations derived based on mechanistic assumptions to give an insight on a reaction mechanism. Most common reaction models are shown in

Table 4.3 41. The oxidation kinetics is studied non-isothermally to determine the kinetic behavior of the materials over the temperature range (100 – 1000°C). For non-isothermal experiments with constant heating rates ( = dT/dt), the kinetic equation becomes

퐸 푑훼 퐴 − 푎 (4.3) = 푒 푅푇푓(훼) 푑푇 훽

The integral form of the kinetic equation is shown in Equation (4.4). Reaction conversion, α, is calculated based on the thermogravimetric data as shown in Equation (4.5).

푇 −퐸 푑훼 퐴 ( 푎) (4.4) 푔(훼) = = ∫ 푒 푅푇 푑푇 푓(훼) 훽 0 푚 − 푚 훼 = 0 푇 (4.5) 푚0 − 푚푓

where g() is the integral form of the reaction model, m0 is the initial weight of the sample, mT is weight at temperature T, mf is the final weight.

Table 4.3. Solid-state reaction models in differential from. Kinetic model Kinetic mechanism 풇(휶) P2 Power law 2훼(1/2) P3 Power law 3훼(2/3) P4 Power law 4훼(3/4) An Avrami-Erofeev 푛(1 − 훼)[−ln (1 − 훼)](n−1/n) R2 Contracting area 2(1 − 훼)1/2 R3 Contracting volume 3(1 − 훼)2/3 D1 1-D diffusion 1/(2훼) D2 2-D diffusion [−ln (1 − 훼)]−1 D3 3-D diffusion-Jander 3/2(1 − 훼)2/3[1 − (1 − 훼)1/3]−1 D4 Ginstling-Brounshtein 3/2[(1 − 훼)−1/3 − 1] 푛 Fn Reaction order of n (1 − 훼)

Kinetic parameters can be estimated by fitting the non-isothermal kinetic equation to the experimental data using a nonlinear regression analysis. The selection of the best-fitted reaction model is supported by XRD analyzes of the redox materials. XRD analyses are performed on reduced materials and 20%, 50% and 100% conversion oxidized materials.

4.4. Results and discussion

4.4.1. Characterization of spray-dried particles

SEM images of the spray-dried candidate materials before calcining are shown in

Figure 4.1. Spray-drying a pure manganese oxide slurry with no added secondary colloidal suspension produces few spherical particles, and instead yields mostly flakes (Figure 4.1a).

Including 30wt% of Al2O3, ZrO2, or Fe2O3 as added colloidal suspensions in the spray drying slurry results in a significant fraction of spherical particles (Figure 4.1b–d), along with needle- like and oblong formations. Including 67wt% of Fe2O3 as a colloidal suspension leads to the formation of a very large fraction of polydisperse spherical particles with nearly no formation of needles, oblong formations, or any other non-spherical shapes. Addition of colloidal suspensions to the manganese oxide slurries appears to have helped spherical particles form; this is consistent with prior work in which a colloidal boehmite binder produced spherical particles with higher mechanical strength than alumina nanoparticle slurries 36

Figure 4.1. SEM images of spray-dried particles before calcine: a) NS, b) Al30, c) Zr30, d) Fe67.

SEM images of the spray-dried candidate materials after calcining at 1200°C for 8 hours are shown in Figure 4.2. The selection of the secondary oxide used in the spray-drying process

strongly influences how well particles retain their original shape and resist sintering during calcining. Comparison of the morphologies in Figure 4.1 and Figure 4.2 shows that NS (a) and

Fe67 (d) lose spherical particle shape entirely after calcination. Al30 (b) and Zr30 (c) retain some spherical particles. This could be attributable to some materials (Al30 and Zr30) maintaining separate support phases that help to maintain this morphology, whereas materials that combine to form a single mixed-metal phase (NS, Fe67; this is discussed below) might not be able to maintain spherical particle morphology.

Figure 4.2. SEM images of spray-dried particles after calcine at 1,200°C for 8 hours: a) NS, b) Al30, c) Zr30, d) Fe67. Fe67 particles produced by the intensive mixing method have a wide size distribution.

These particles are sieved through a sequential series of mesh sizes. SEM images of two different size ranges (x<25 µm and 100

Figure 4.3. Unlike the Fe67 materials prepared by spray-drying and the smaller particles (> 25

µm) prepared by intensive-mixing maintained a fairly spherical morphology after calcination as shown in Figure 4.3b.

Figure 4.3. SEM images of Fe67 prepared by intensive mixing after calcine at 1,200°C for 8 hours: a) x < 25 µm, b) 100 < x < 500 µm The measurement of BET surface area for spray-dried particles reveals a significant reduction in particle surface area after calcining (Table 4.4). The surface area for the Fe67_IM (x

< 25 µm) is comparable with the surface area of Fe67_SD.

Table 4.4. BET surface area (before and after calcining) and particle size distribution for spray dried candidate materials after calcining at 1,200°C. BET Surface Area (m2/g) Sample ID Pre-Calcine Post-Calcine NS 10.22 0.37 Al30 69.87 1.28 Zr30 64.75 0.74 Fe67_SD 54.97 0.61 Fe67_IM (x < 25 µm) N/A 0.69

The XRD spectra for the calcined candidate materials are displayed in Figure 4.4. The pure manganese oxide material, NS, shows peaks corresponding to the Mn3O4 spinel phase.

XRD peaks that do not match the Mn3O4 spinel phase seem to correspond well with a mixed

Mn/Na oxide phase, as shown in the figure. ICP-OES analysis was conducted to check for the presence of Na in the spray dried particles. Results of this analysis are discussed subsequently in conjunction with thermodynamic predictions for the inclusion of Na, which predict a mixed- metal slag phase that may present as XRD crystal peaks.

Mixed metal oxide Al30 has peaks corresponding to a mixed manganese aluminum oxide spinel (MnAl2O4) and a mixed Na/Mn oxide phase, similar to NS. XRD spectra of Zr30 indicate that manganese oxide and zirconia do not form solid solutions at 1200C. Zirconia in the sample consists of a mixture of monoclinic and tetragonal ZrO2. Manganese oxide is present in the Zr30 sample as the Mn3O4 spinel phase. Fe67 spectra indicate that both samples prepared by spray- drying and intensive mixing are entirely composed of MnFe2O4 spinel.

Figure 4.4. X-ray diffraction spectra for spray-dried candidate materials after calcining at 1,200°C 4.4.2. Thermodynamic predictions for candidate materials

In order to gain a more complete understanding of the effect of secondary metal oxide additives to the manganese oxide active materials, thermodynamic predictions for each material

were generated using the FactSage software. Predictions of the favored metal oxide phases present under given temperature and atmospheric conditions encompassing the calcining process and subsequent redox cycling conditions (400–1,400C under air and N2 atmospheres) are shown in Figure 4.5. Sodium was not included in these predictions, as future efforts will likely not include the same amount of sodium contamination. Additionally, the predicted phases that included Na were so small as to not easily display on the graphs below; thus, Na was not included for both clarity and future usefulness.

The thermodynamic predictions show that the reduction temperature (the temperature at which the manganese oxide reduces and mass is lost) shifts up to a higher temperature for the air atmosphere relative to the inert atmosphere for each material composition considered here. The environment around the metal oxide can become more reducing due to higher temperatures or a lower oxygen partial pressure. By contrast, the phase transition between α-Mn3O4 and β-Mn3O4 appears to be independent of both the secondary oxide used and the gaseous atmosphere, and instead occurs at a fixed temperature. Zirconia does not form a solid solution with manganese oxide up to ~1,300°C under either air or an inert atmosphere, instead the zirconia and manganese oxide maintain separate phases. This prediction is supported by the XRD spectra for Zr30 calcined in air at 1,200°C, which shows no indication of the presence of a mixed metal oxide.

Alumina partially forms a mixed bixbyite phase with manganese oxide (Mn,Al)2O3 at temperatures below 700°C in N2 and below 1,050°C in air. Above these temperatures, pure manganese oxides are formed. In addition, MnAl2O4 spinel is formed above ~750°C in N2 and above ~980°C in air. XRD spectra corroborate the formation of a mixed (Mn,Al)3O4 spinel phase during calcination in air, and also confirm that all added alumina is incorporated into the solid

solution. Iron oxide is predicted to form entirely mixed metal oxide phases for the Fe67 composition.

Figure 4.5. Thermodynamic predictions of reduction and oxidation behavior of candidate materials in air and inert environments.

4.4.3. Thermogravimetric analysis

Greater repeatable mass change during redox cycling corresponds to higher oxygen exchange (whereas other effects such as material sublimation would appear irreversible), which is an indication of higher chemical storage capacity. The results from the TGA redox cycling tests are summarized in Figure 4.6. Fe67_SD, Fe67_IM, and NS outperform the other candidate materials at all reduction temperatures in terms of their specific mass change during cycling.

Zr30 performs best at a reduction temperature of 1,100°C; however, the mass change decreases at a reduction temperature of 1,200 °C. Al30 performs best at a reduction temperature of

1,200°C and does not exhibit a decrease in mass change over six redox cycles for both reduction temperatures.

Figure 4.6. Thermogravimetric analysis for candidate active materials over six redox cycles, with oxidation at 650°C and reduction at 1,100°C, and 1,200°C. Plots at the top of each column show the temperature profile, and plots below show the specific mass change of the sample during redox cycling. The mass change during reduction and oxidation for the top performing candidate materials Fe67, and NS is shown Figure 4.7. Neither Fe67_SD nor Fe67_IM exhibit a decrease in mass change over six cycles at both reduction temperatures tested; however, the mass change slightly decreases for NS during repeated reduction at 1,100°C and 1,200°C. Fe67 materials prepared by spray-drying and intensive mixing outperform the other candidate materials at all reduction temperatures. However, Fe67 prepared by intensive mixing outperforms spray-dried

Fe67 particles for both reduction temperatures.

Figure 4.7. Mass change for top performing candidate materials over six redox cycles. Theoretical maximum mass change for complete reduction is shown by solid lines. It is likely that most of the samples do not display significant decreased apparent mass loss over six redox cycles because the particles have already undergone significant sintering and surface area loss during the calcining process. Loss of surface area before TGA testing could be responsible for the lower than theoretically predicted mass loss results (Figure 4.7).

Compositional analysis using ICP-OES of candidate materials lends further credence to this

theory, and provides a possible explanation for the unexpectedly high amount of particle sintering and the lower than expected mass loss. Elemental analysis revealed that the Mn2O3 nanopowder used to make the spray-dried particles contains sodium (~0.5 wt%). Precursor slurries were also tested for sodium, and were found to contain similar sodium levels regardless of whether or not they had been pH tuned with 1M NaOH. Elemental analysis for the Mn3O4 powder used to make the intensive mixing particles has a sodium content less than 100 ppm.

This explains why Fe67 particles prepared by intensive mixing have higher specific mass change than Fe67 particles prepared by spray-drying.

These findings underscore the importance of sourcing pure materials when producing spray dried active particles. Including this sodium contamination in thermodynamic predictions of candidate materials dramatically reduces the predicted slagging temperatures for several of these materials, shown in Table 4.5; in the case of NS and Zr30, slagging is predicted at < 800°C in air. This will drastically reduce surface area available for reaction. The inert ZrO2 support material is likely the reason for the somewhat reduced visible sintering of Zr30 particles compared to NS particles, which possess no protective support structure. Na contamination was not predicted to have much of an impact on Fe67 material, however it was shown to have an impact on the redox cycling at both reduction temperatures.

Table 4.5. Thermodynamic predictions of slagging temperatures of candidate materials in air and inert environments with and without Na contamination in the Mn2O3 powder. Predicted Slagging Temperature (°C) Candidate No Na Addition 0.5 wt% Na in Mn2O3 Material Air Air N Atmosphere N Atmosphere 2 Atmosphere 2 Atmosphere NS 1,657 1,581 666 785 Al30 1,455 1,465 1,346 1,365

Zr30 1,457 1,499 662 785

Fe67 1,565 1,594 1,578 1,598

4.4.4. Fe67 Oxidation Kinetics

Four runs at different heating rates were carried out to extract kinetic data on the oxidation of Fe67 materials with air. Fe67 prepared by the intensive mixing method was used for the kinetics study. A smaller particle size (x < 25 µm), as shown in Figure 4.3a, was chosen for the oxidation study to minimize the impact of oxygen gas diffusion inside the particles.

4(푀푛0.33퐹푒0.67)3푂4 + 푂2 → 6(푀푛0.33퐹푒0.67)2푂3 (4.6)

Figure 4.8a) depicts the conversion versus temperature plots of the Fe67 oxidation reaction. Isoconversional analysis allows for the calculation of activation energy as a function of conversion without prior knowledge of a physical model, f(α). This is done by taking the natural logarithm of the reaction rate shown in Equation (4.4). Since the reaction rate equation has an integral that does not have an analytical solution, several approximations have been proposed which give rise to a linear equation. Two accurate approximations, Kissinger-Akahira-Sunose

(KAS) and Starink, were applied to calculate the activation energy as shown in Equations (4.7) and (4.8), respectively 42.

훽푖 퐸푎 (4.7) ln ( 2 ) = 퐶표푛푠푡 − 푇훼,푖 푅푇훼 훽푖 퐸푎 (4.8) ln ( 1.92) = 퐶표푛푠푡 − 1.0008 푇훼,푖 푅푇훼

The activation energy at each given α is determined from the slope of the two equations.

All plots for each given α resulted in a linear relationship with a high correlation coefficient (>

99%). Figure 4.8b) provides the results of the isoconversional computations of Fe67 oxidation reaction at incremental conversion values of 5%.

Figure 4.8. a) α versus temperature plots for oxidation of fe67 materials at multiple heating rates. b) Ea versus α calculated using KAS and Starink isoconversional methods

Isoconversional kinetic analysis using the KAS and Starink methods shows two distinct regions where the calculated activation energies differ in value. The first region is from 5% to

30% conversion where the average activation energy is 200 ± 9 kJ mol-1. The second region is from 30% to 80% where the activation energy is 179 ± 3 kJ mol-1. The reaction rate suffered a deceleration above 85% conversion at around 700°C. Similar behavior was observed in the oxidation kinetics study of (Mn0.8Fe0.2)3O4 by Carrillo et al where the oxidation rate suffered a deceleration in the temperature range from 725°C to 800°C 43. Therefore, we will attempt to extract the kinetic data of the reaction for the conversion data from 1 – 80%.

To get further insight about the reaction mechanism of Fe67 oxidation, XRD analyses were performed on reduced, 20%, 50% and 100% oxidized samples and are shown in Figure 4.9.

Figure 4.9. X-ray diffraction spectra of Fe67 at reduced, 20% 50% and 100% oxidized states. (B = Bixbyite, (Mn,Fe)2O3, J = jacobsite, MnFe2O4)

The XRD spectra for reduced Fe67 shows peaks corresponding to the MnFe2O4 spinel phase (jacobsite). XRD analysis of the 20% oxidized Fe67 reveals no phase change. However, the spinel peaks shift slightly to higher 2θ positions, which indicates lattice contraction. In the

50% oxidized sample, the formation and precipitation of a new phase (bixbyite) is observed along with some of the spinel peaks. All powders are transformed to a bixbyite phase,

(Mn,Fe)2O3, phase in the 100% oxidized sample. XRD analyses show that the Fe67 oxidation proceeds by two different mechanism, no phase change and the precipitation of multi-oxide phases. This finding is corroborated by the isoconversional kinetic analysis where two regions with different activation energies are observed. Furthermore, examining the α versus temperature graph shown in Figure 4.8a closely show that there is a change in the slope of the lines at around

30% conversion.

First, direct model fitting of the experimental data (α = 1 – 80) to Equation (4.3) was carried out by minimizing the sum of quadratic residuals (SQR). Table 4.6 and Figure 4.10 show the results of the four models that has the lowest SQR. However, none of these models gave a satisfactory fit for the Fe67 oxidation reaction. Furthermore, none of the calculated activation

energies for the different models are close the calculated activation energy using the isoconversional method.

Table 4.6. Kinetic parameters calculated for the best individual fitting of the experimental at β = 10.0°C/min. log (A) Ea SQR D3 4.5 110 34 F2 2.0 65 16 P2 -0.6 15 78 R3 1.3 49 36

Figure 4.10. Comparison between the experimental TGA results at β = 10.0°C/min and calculated data using D3, F2, P2 and R3 fitting models

Based on the findings from the isoconversional kinetic and XRD analyses, the Fe67 oxidation reaction shown in Equation 6 will split into two reactions shown in Equation (4.9) (no phase change) and Equation (4.10) (forming new phases). Similar observation was made in a previous study, where defect spinel was formed before the formation of a new phase upon

44 oxidation of MnFe2O4 .

훿 (4.9) (푀푛 퐹푒 ) 푂 + 푂 → (푀푛 퐹푒 ) 푂 0.33 0.67 3 4 2 2 0.33 0.67 3 4+훿

4(푀푛0.33퐹푒0.67)3푂4+훿 + (1 − 2훿)푂2 → 6(푀푛0.33퐹푒0.67)2푂3 (4.10)

Now, direct model fitting of the experimental data is applied to the two different regions

(α = 0 – 30% and α = 30 – 80%) using a multivariate nonlinear regression analysis to fit simultaneously the data for the four heating rate experiments. Table 4.7 summarizes the results obtained for the best fitting model along with the fitted kinetic parameters and SQR.

Table 4.7. Kinetic parameters calculated for the best individual fitting of the experimental data for two different regions. α = 0.0 - 0.30 α = 0.30 - 0.8

β D3 A0.5

(°C/min) log(A) Ea RSQ log(A) Ea RSQ

2.5 4.7 0.6

5.0 4.4 0.7 11.75 ± 0.04 192 ± 2 9.65 ± 0.06 181.4 ± 0.3 7.5 4.2 0.8

10.0 4.6 0.6

Figure 4.11 shows that the first reaction is well described by the D3 model, while the second reaction is described by an Avrami-Erofeev, AE0.5, model. Furthermore, the activation energies found for both models are close to the activation energies calculated using the isoconversional methods.

Figure 4.11. TGA experimental data and predictions with kinetic order model at different heating rates a) 2.5, b) 5.0, c) 7.5 and d) 10.0°C/min

The kinetic analysis just described suggests that the rate of the first reaction, at (0 – 30%

α), is limited by the mobility of lattice constituents. Kester et al. showed that the oxidation of

MnFe2O4 to MnFe2O4+δ reaction is limited by a vacancy diffusion-controlled process. In this process, Oxygen gas disassociates onto the surface. This is followed by incorporation of O into the lattice and the diffusion of cations to the surface 45. Gillot et al. showed during the non-phase change oxidation for Fe67, all Fe2+ and Mn3+ ions on the octahedral sites and partial Mn2+ ions on the tetrahedral sites are oxidized 46. The appearance of the precipitated bixbyite phase in the

XRD at 50% reaction conversion confirms the change in reaction mechanism and it is consistent with the change in the calculated activation energy using the isoconversional analysis. In the

second kinetic region, the conversion curve appears to have a sigmoidal shape, where an

Avrami-Efrofeev model best fit the experimental data with an Avrami exponent n of 0.5. This value describes a linear diffusion-controlled growth and instant nucleation at the beginning of the phase transformation 47.

To study the effect of particle size on the reaction kinetics, oxidation of two different reduced Fe67 particle sizes (x< 25 µm and ~ 300 µm) were carried out. Figure 4.12 shows the conversion versus temperature plots of the Fe67 oxidation reaction for the two different particle sizes.

Figure 4.12. α versus temperature plots for oxidation of two different particle sizes fe67 materials at 10˚C/min

As we can see from the graph, the particle size has an effect on the second reaction mechanism where the reaction follows a nucleation and growth reaction mechanism. The reaction rate did not change when the reaction rate is controlled by cation diffusion for the bigger particle size. Figure 4.13 presents the schematic description of diffusion family and nucleation

(Avrami-Efrofeev) family models. As mentioned before, the O2 gas adsorbs to the reduced Fe67 surface and dissociates into free O atoms. In the diffusion model, the reaction is limited by the

cation diffusion through the lattice and it appears the reaction rate is not affected by the bigger particle size. In the Avrami family models, the reaction proceeds by nuclei formation and subsequent nuclei growth upon oxygen adsorption on the reduced surface 41. We can see from the α versus temperature graph, the reaction rate is slower for the larger particle size. This can be attributed to less surface area exposed to the disassociated O atoms which will limit the rate of nuclei formation.

Figure 4.13. Schematic description of (a) diffusion family models and (b) Avrami-Efrofeev family models These results demonstrate the benefit of operating the redox cycle through a cation- vacancy mechanism where the spinel phase maintain its crystal structure. The reaction rate was shown to be stable regardless of particle size. This will give more room in designing a reactor that needs a larger reactive particle sizes. However, the specific mass change will be lower if the redox cycling is limited to the cation-vacancy reaction mechanism.

4.5. Conclusions

This study shows a trade-off between spray dried particle robustness during redox cycling and particle activity. While candidate materials with added alumina and zirconia retained better individual particle structure after being heated to 1,200°C, they did not perform as well during redox cycling. Conversely, pure manganese oxide was unable to reliably form spray dried particles without the help of a colloidal suspension, and thus calcining the material produced mostly sintered agglomerates; however, these particles showed good redox activity. Manganese oxide with iron oxide in a molar ratio of 1:2 was able to form spherical spray dried particles which agglomerated and lost spherical shape during calcining, but also exhibited the best activity of any candidate material tested. This thermochemical performance was obtained over multiple cycles despite this apparent loss of surface area. Sodium contamination of the spray dried particles showed to have an effect on the redox cycling and particle morphology at high reduction temperatures.

Zirconia appears to function as a stable solid support material at the temperatures tested, and did not form a solid solution with manganese oxide. This provides an opportunity for inclusion of zirconia as an inert support for higher activity materials. Alumina and iron oxide both formed mixed metal oxide spinels with manganese oxide after calcining.

During TGA cycling experiments, the candidate material Fe67 prepared by intensive mixing, a manganese iron oxide spinel with a 1:2 Mn:Fe molar ratio, outperformed spray-dried pure manganese oxide by a factor of 1.8 in terms of specific mass change. The materials also retained their spherical morphology unlike the spray-dried Fe67 materials which were contaminated with sodium.

The oxidation of reduced Fe67 in air has been studied in the TGA. Isoconversional and

XRD analyses show the reaction has two different reaction mechanisms. The reaction first follows a Jander diffusion model where the reaction rate is limited by the cation diffusion. The reaction mechanism changes to a nucleation and growth model where the rate is described by an

Avrami-Erofeev model with an exponent of 0.5. Activation energies determined by model fitting methods were close the activation energies calculated by the isoconversional methods. We also show that operating the redox cycle through the cation-vacancy mechanism with no phase change is more stable than when changing phases mechanism.

4.6. References

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23. Linderholm C, Mattisson T, Lyngfelt A. Long-term integrity testing of spray-dried particles in a 10-kW chemical-looping combustor using natural gas as fuel. Fuel. 2009;88(11):2083-2096. 24. Walton DE, Mumford CJ. Spray Dried Products—Characterization of Particle Morphology. Chemical Engineering Research and Design. 1999;77(1):21-38. 25. Liu B, Zhang X, Wang L, Hong H. Fluidization of non-spherical particles: Sphericity, Zingg factor and other fluidization parameters. Particuology. 2008;6(2):125-129. 26. Hruby JM. A Technical Feasibility Study of a Solid Particle Solar Central Receiver for High Temperature Applications. Sandia National Laboratories;1986. SAND86-8211. 27. Nandiyanto ABD, Okuyama K. Progress in developing spray-drying methods for the production of controlled morphology particles: From the nanometer to submicrometer size ranges. Advanced Powder Technology. 2011;22(1):1-19. 28. Wokon M, Block T, Nicolai S, Linder M, Schmücker M. Thermodynamic and kinetic investigation of a technical grade manganese-iron binary oxide for thermochemical energy storage. Solar Energy. 2017;153:471-485. 29. Wokon M, Kohzer A, Linder M. Investigations on thermochemical energy storage based on technical grade manganese-iron oxide in a lab-scale packed bed reactor. Solar Energy. 2017;153:200-214. 30. Babiniec SM, Coker EN, Miller JE, Ambrosini A. Investigation of LaxSr1−xCoyM1−yO3−δ (M = Mn, Fe) perovskite materials as thermochemical energy storage media. Sol Energy. 2015;118:451-459. 31. Babiniec SM, Coker EN, Miller JE, Ambrosini A. Doped calcium manganites for advanced high-temperature thermochemical energy storage. International Journal of Energy Research. 2016;40(2):280-284. 32. Imponenti L, Albrecht KJ, Braun RJ, Jackson GS. Measuring thermochemical energy storage capacity with redox cycles of doped-CaMnO3. ECS Transactions. 2016;72(7):11- 22. 33. Carrillo AJ, Serrano DP, Pizarro P, Coronado JM. Improving the Thermochemical Energy Storage Performance of the Mn2O3/Mn3O4 Redox Couple by the Incorporation of Iron. ChemSusChem. 2015;8(11):1947-1954. 34. Azimi G, Leion H, Mattisson T, Lyngfelt A. Chemical-looping with oxygen uncoupling using combined Mn-Fe oxides, testing in batch fluidized bed. Energy Procedia. 2011;4:370-377. 35. Bertrand G, Roy P, Filiatre C, Coddet C. Spray-dried ceramic powders: A quantitative correlation between slurry characteristics and shapes of the granules. Chemical Engineering Science. 2005;60(1):95-102. 36. Kanerva U, Suhonen T, Lagerbom J, Levänen E. Evaluation of crushing strength of spray-dried MgAl2O4 granule beds. Ceramics International. 2015;41(7):8494-8500.

37. Bale CW, Bélisle E, Chartrand P, et al. FactSage thermochemical software and databases — recent developments. Calphad. 2009;33(2):295-311. 38. Eriksson G, Hack K. ChemSage—A computer program for the calculation of complex chemical equilibria. MTB. 1990;21(6):1013-1023. 39. Allendorf MD, Diver RB, Siegel NP, Miller JE. Two-Step Water Splitting Using Mixed- Metal Ferrites: Thermodynamic Analysis and Characterization of Synthesized Materials. Energy & Fuels. 2008;22(6):4115-4124. 40. Khawam A, Flanagan DR. Basics and applications of solid‐state kinetics: A pharmaceutical perspective. Journal of pharmaceutical sciences. 2006;95(3):472-498. 41. Khawam A, Flanagan DR. Solid-state kinetic models: basics and mathematical fundamentals. The journal of physical chemistry B. 2006;110(35):17315-17328. 42. Vyazovkin S, Burnham AK, Criado JM, Pérez-Maqueda LA, Popescu C, Sbirrazzuoli N. ICTAC Kinetics Committee recommendations for performing kinetic computations on thermal analysis data. Thermochimica Acta. 2011;520(1):1-19. 43. Carrillo AJ, Serrano DP, Pizarro P, Coronado JM. Understanding redox kinetics of iron- doped manganese oxides for high temperature thermochemical energy storage. The Journal of Physical Chemistry C. 2016;120(49):27800-27812. 44. Gillot B, Laarj M, Kacim S. Reactivity towards oxygen and cation distribution of manganese iron spinel Mn 3-x Fe x O 4 (0≤ x≤ 3) fine powders studied by thermogravimetry and IR spectroscopy. Journal of Materials Chemistry. 1997;7(5):827- 831. 45. Kester E, Perriat P, Gillot B, Tailhades P, Rousset A. Correlation between oxidation states of transition metal ions and variation of the coercivity in mixed-valence defect spinel ferrites. Solid state ionics. 1997;101:457-463. 46. Gillot B, El Guendouzi M, Kharroubi M, Tailhades P, Metz R, Rousset A. Phase transformation-related kinetic in the oxidation of a manganese mixed oxide with a spinel structure. Materials chemistry and physics. 1989;24(1-2):199-208. 47. Cumbrera F, Sanchez-Bajo F. The use of the JMAYK kinetic equation for the analysis of solid-state reactions: critical considerations and recent interpretations. Thermochimica acta. 1995;266:315-330.

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CHAPTER 5

5. CONCLUSIONS AND RECOMMENDATIONS FOR FUTURE WORK

5.1. Summary and conclusions

The work presented here evaluates two types of spinel metal oxide materials for high temperature solar thermochemical cycles. The hercynite materials was investigated for use in solar thermochemical water splitting and iron manganese oxide was investigated for use in solar thermochemical energy storage. The findings of the individual objectives are briefly summarized below.

5.1.1. The chemistry and reduction kinetics of the hercynite cycle

Isoconversional and XRD analyses show the reaction has two different reaction mechanisms.

The reaction first follows a nucleation and growth model where the rate is described by an

Avrami-Erofeev model with an exponent of 1. The reaction mechanism changes to a third-order reaction model, where the reaction rate is limited by the concentration of cation vacancies.

101

5.1.2. Iron manganese oxide for solar thermochemical energy storage

In this work, we evaluate the effect of three secondary metal oxides (Al2O3, ZrO2, and Fe2O3) on the redox behavior and sintering temperatures of manganese-oxide-based materials.

1,200°C, to evaluate the impact of the different secondary metal oxides on chemical activity and robustness of the particles. In this work, we also study the oxidation kinetics of the iron manganese oxide materials in air using TGA and XRD. XRD analyses of the materials provide an insight on the crystal transformation of the materials during the oxidation reaction.

Sodium contamination of the spray dried particles showed to have an effect on the redox cycling and particle morphology at high reduction temperatures. During TGA cycling experiments, the candidate material Fe67 prepared by intensive mixing, a manganese iron oxide spinel with a 1:2 Mn:Fe molar ratio, outperformed spray-dried pure manganese oxide by a factor of 1.8 in terms of specific mass change. The materials also retained their spherical morphology unlike the spray-dried Fe67 materials which were contaminated with sodium.

The oxidation of reduced Fe67 in air has been studied in the TGA. Isoconversional and XRD analyses show the reaction has two different reaction mechanisms. The reaction first follows a

Jander diffusion model where the reaction rate is limited by the cation diffusion. The reaction mechanism changes to a nucleation and growth model where the rate is described by an Avrami-

Erofeev model with an exponent of 0.5. Activation energies determined by model fitting

102

methods were close the activation energies calculated by the isoconversional methods. We also show that operating the redox cycle through the cation-vacancy mechanism with no phase change is more stable than when changing phases mechanism.

5.2. Recommendations for Future Work

Much progress has been made in solar thermochemical cycles field, both in water splitting and energy storage. Although the two processes have the ability to achieve high theoretical efficiencies, they face significant technical challenges before scaling up to industrial size plant is realized. The biggest challenge is design and build a reactor that can withstand the high temperatures required for the thermal reduction of the redox materials. Several reactor designs have been proposed for high temperature water splitting and energy storage cycles but they need to be experimentally validated. Solar simulators may be helpful in this aspect to test a lab bench scale reactors. Another big challenge with high temperature solar reactors is the possible rapid change of solar flux due to intermittent clouds. Complicated control systems may be required to track sun and cloud movements and predict solar flux changes to minimize the impact of the rapid solar flux changes and avoid catastrophic failures.

Developing a thermodynamic model to estimate solar to hydrogen efficiencies is essential.

Ehrhart et al. have developed a comprehensive model to estimate the solar to hydrogen efficiencies for ceria and ferrite/zirconia materials. It was shown that process efficiencies depend on the materials and its kinetics. Future research should focus on the development of process efficiencies for the hercynite materials. In this work we have shown that the hercynite redox cycle undergoes a cation vacancy mechanism rather than stoichiometric and O-vacancy mechanisms. Predicting the thermodynamic hydrogen capacity of the hercynite materials is essential for the solar to hydrogen efficiency calculations. This will depend on the reduction

103

temperature and the oxygen partial pressure and it can be done using thermogravimetric analysis study. Similar process efficiencies model can also be developed for the solar thermochemical energy storage system.

Understanding that the reaction mechanism of hercynite and Fe67 spinels undergoes a cation- vacancy mechanism can help efforts of computation simulations to predict spinel-type materials that can split water and or carbon dioxide. Performing computation simulations with the assumption of cation vacancy mechanism for the spinel materials will help with materials discovery efforts. Also, hercynite cycle can be improved by doping it with other materials to tune its properties. Doping the hercynite with cobalt was shown to lower the hydrogen capacity, but increase the oxidation reaction rate. Similar computational analysis can be applied to the redox material discovery for solar thermochemical energy storage.

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