Co2 (H2s)-Selective Membranes for Fuel Cell Hydrogen

CO2 (H2S)-SELECTIVE MEMBRANES FOR FUEL CELL HYDROGEN

PURIFICATION AND FLUE GAS CARBON CAPTURE:

AN EXPERIMENTAL AND PROCESS MODELING STUDY

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

Kartik Ramasubramanian

Graduate Program in Chemical and Biomolecular Engineering

The Ohio State University

2013

Dissertation Committee:

Dr. W.S. Winston Ho (Advisor)

Dr. Stuart Cooper

Dr. David Tomasko

Kartik Ramasubramanian

2013

Abstract

CO2 capture from fuel and flue gases is critical to reducing the anthropogenic influence on climate change. Solvent absorption-, adsorption- and membrane-based processes have been widely studied for this application. Compared to the former two alternatives which are equilibrium-based, membrane separation is rate-based and does not involve phase change. Membranes hold great promise for CO2 capture due to their potentially lower energy consumption compared to other processes, operational simplicity with no handling of steam and condensed phases, lower water consumption, compactness, and ease of maintenance due to absence of moving parts.

CO2 (H2S)-selective membranes with appropriate separation capabilities can be used to separate CO2 from waste gases in a fossil fuel-based power plant or both CO2 and

H2S from syngas streams containing hydrogen. They can also be integrated with water gas shift (WGS) reaction for effective CO, CO2 and H2S clean up. In the context of hydrogen purification for fuel cells, a detailed 2-D model incorporating mass, energy and pressure drop equations for describing the transport in an intricate spiral-wound WGS membrane reactor was developed and validated using prior experimental data. Such a configuration is also used in state-of-the-art water purification processes and was the preferred choice for the advanced gas separation membranes studied in this work. A simplified 1-D version of the same model was then combined with a detailed cost ii methodology to study the feasibility of membrane processes for post-combustion CO2 capture (PCC) in a coal-based power plant. From this study, valuable insights into the membrane properties required to meet the economic goals of PCC were gained.

As a part of the experimental work, we first scaled up an existing amine-based facilitated transport membrane to purify hydrogen for fuel cells. The membranes were then characterized for their separation performance using a gas permeation set-up and compared with lab-scale membranes. Later, we focused on developing membranes for

PCC. It is known that inorganic membranes can offer advantageous separation/substrate capabilities while lacking the ease of scale-up and economic viability of polymer membranes. Driven by the idea to combine the good qualities of the above two types of membranes, detailed protocols for depositing thin (<1 μm) zeolite Y layers (~40 and

~200 nm particle sizes) on polymer supports were developed. The effects of support surface morphology (pore size and surface porosity), inorganic particle size and layer thickness on the quality of deposition were studied using imaging via optical as well as electron microscopy. Lastly, the above multilayer hybrid materials were used as substrates for amine-based selective layers. In order to improve the membrane for PCC, different amines were used and compared on the basis of their separation capabilities.

Also, the membrane tolerance towards SO2, a common minor component in flue gas, was studied by continuous monitoring of separation performance in the presence of simulated gas mixtures with different SO2 levels.

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Dedicated to my parents, my sisters Gayatri and Shanta, and to Akanksha

Acknowledgments

I would start by thanking my advisor, Dr. W.S. Winston Ho for his passion and drive towards research, and for expecting me to show the same at all the times through all these years. His support, encouragement and guidance have been crucial in shaping not only my dissertation research but also my overall development as a professional researcher.

I am grateful to Dr. Hendrik Verweij for serving on my qualifier committee and both him and Dr. Prabir Dutta for their valuable insights on my work. I am thankful to

Dr. Kurt Koelling for being a part of my qualifier and candidacy examination committees. I am also grateful to Dr. Stuart Cooper and Dr. David Tomasko for being a part of my candidacy and final defense exams. Their willingness to evaluate this work is highly appreciated.

I would specially like to thank Paul Green and Leigh Evrard for being invaluable assets to our group‟s research efforts and also for my personal research work. Their willingness to explore new solutions and go out of their way to use their skills for others cannot be thanked enough.

I would also like to thank my colleagues; Yanan Zhao, Lin Zhao, Yuanxin Chen,

Varun Vakharia, Zi Tong, and others. Special thanks to Lin Zhao and Varun Vakharia for

v playing indispensable roles in the scale-up project. It was a team effort and I was thoroughly fortunate to have led a talented team of fellow graduate students. I am also thankful to visiting colleagues; Dr. Chunhai Yi and Luca Ansaloni for being a part of this journey. Additionally, I thank my roommates, Ashutosh Bhabhe and Shreyas Rao, and all my friends in the department for their help and understanding throughout this PhD.

This work would not have been possible without the love, affection, support and faith of my family including my amma, appa, periamma, periappa, and my sisters,

Gayatri and Shanta. Last, but most certainly not the least, I would like to thank Akanksha

Kanitkar for always being there for me, patiently, through all these years. Without her, this PhD would have been impossible.

Vita

1985………………………………………....Born – Mumbai, Maharashtra, India

2007...... B. Chem. Eng., Institute of Chemical

Technology (formerly UDCT), Mumbai,

India

2007 to present ...... Graduate Research Associate, Department

of Chemical and Biomolecular Engineering,

The Ohio State University

Publications

1. K. Ramasubramanian, M. Song and W. S. W. Ho, “A Spiral-Wound Water-Gas-Shift Membrane Reactor for Fuel-Cell Hydrogen Purification”, Industrial & Engineering Chemistry Research, 10.1021/ie302424y, 52, 8829-8842 (2013).

2. K. Ramasubramanian, Y. Zhao and W.S.W. Ho, “CO2 Capture and H2 Purification: Prospects for CO2-Selective Membrane Processes”, AIChE Journal, doi:10.1002/aic.14078, 59 (4), 1033-1045 (2013).

3. K. Ramasubramanian, H. Verweij and W. S. W. Ho, “Membrane Processes for Carbon Capture from Coal-Fired Power Plant Flue Gas: A Modeling and Cost Study”, Journal of Membrane Science, 10.1016/j.memsci.2012.07.029, 421–422, 299- 310 (2012).

4. K. Ramasubramanian and W. S. W. Ho, “Recent Developments on Membranes for Post-combustion Carbon Capture”, Current Opinion in Chemical Engineering, 10.1016/j.coche.2011.08.002, 1 (1), 47-54 (2011).

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5. Y. Zhao, K. Ramasubramanian, and W. S. W. Ho, “Carbon Dioxide-Selective Membranes for Hydrogen Purification for Fuel Cells”, Preprints of Symposia - American Chemical Society, Division of Fuel Chemistry, 56 (1), 343-346 (2011).

6. H. Bai, K. Ramasubramanian, and W. S. W. Ho, “H2S- and CO2-Selective Membranes for Fuel Processing for Fuel Cells”, Preprints of Symposia - American Chemical Society, Division of Fuel Chemistry, 54 (2), 820-822 (2009).

Fields of Study

Major Field: Chemical and Biomolecular Engineering

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Table of Contents

Abstract ...... ii Dedication ...... iv Acknowledgments...... v Vita………………………………………………………………………………………vii Publications ...... vii Fields of Study ...... viii List of Tables ...... xiv List of Figures ...... xvii List of Notations ...... xxii

CHAPTER 1 ...... 1 INTRODUCTION ...... 1

1.1 Overview ...... 1 1.2 Outline and scope ...... 5

CHAPTER 2 ...... 10 SPIRAL-WOUND WATER-GAS-SHIFT MEMBRANE REACTOR FOR HYDROGEN PURIFICATION ...... 10

2.1 Summary ...... 10 2.2 Introduction ...... 11 2.3 Spiral-wound configuration with sweep gas ...... 14 2.4 Modeling transport in a spiral-wound membrane reactor ...... 14 2.4.1 Molar balances ...... 18 2.4.2 Enthalpy balances and heat transfer ...... 19 2.4.3 Pressure drop (momentum balance) ...... 23 2.4.4 Boundary conditions and solution procedure ...... 25

2.4.5 Membrane performance ...... 25 2.5 Validation of model with experimental data ...... 26 2.6 Sensitivity study ...... 27

2.6.1 CO2 removal and CO conversion ...... 28 2.6.2 Heat transfer and temperature profiles in the membrane reactor ...... 29 2.6.3 Effects of system parameters on membrane area, hydrogen recovery &..32 pressure drop...... 32 2.6.3.1 Effect of feed pressure………………………………………………...32 2.6.3.2 Effect of sweep-to-feed ratio………………………………………….34 2.6.3.3 Effect of steam-to-CO ratio…………………………………………...35 2.6.3.4 Effects of reaction kinetics vs. membrane permeance………………...36 2.7 Conclusions ...... 37 Acknowledgments...... 38

CHAPTER 3 ...... 60 SCALE-UP OF AN AMINE-BASED POLYMER MEMBRANE FOR ...... 60 FUEL CELL HYDROGEN PURIFICATION ...... 60

3.1 Summary ...... 60 3.2 Introduction ...... 61 3.3 Prior research on the lab-scale ...... 65 3.4 Experimental ...... 67 3.4.1 Materials ...... 67 3.4.2 Membrane preparation ...... 69 3.4.2.1 PVA crosslinking…………………………………………...... 69 3.4.2.2 Carrier solution and final casting solution preparation……………….70 3.4.2.3 Other considerations…………………………………………...... 72 3.4.3 Gelling...... 73 3.4.4 Thin-film casting assembly ...... 74 3.4.5 Gas permeation set-up and transport measurements ...... 76 3.4.5.1 Test conditions…………………………………………...... 77 3.5 Results and discussion ...... 78 3.5.1 Membrane quality and defects ...... 78

3.5.2 Transport characterization ...... 78 3.6 Conclusions ...... 83 Acknowledgments...... 84

CHAPTER 4 ...... 98 MEMBRANE PROCESSES FOR CARBON CAPTURE FROM COAL-FIRED POWER PLANT FLUE GAS: A MODELING AND COST STUDY ...... 98

4.1 Summary ...... 98 4.2 Introduction ...... 99 4.3 Membrane processes for carbon capture ...... 101 4.3.1 Challenges ...... 101 4.3.2 Strategies to increase driving force ...... 102 4.3.2.1 Feed compression…………………………………………………….102 4.3.2.2 Vacuum on the permeate side………………………………………..103 4.3.2.3 Sweep on the permeate side………………………………………….103 4.3.3 Multi-stage air-sweep process...... 104 4.4 Process modeling and economics ...... 105 4.4.1 Membrane process modeling and simulation ...... 105 4.4.2 Economics ...... 109 4.4.2.1 Capital cost estimation………………………………………………109 4.4.2.2 Operating cost estimation……………………………………………111 4.4.2.3 Annualized cost of capture and increase on the cost of electricity…..113 4.5 Cost sensitivity ...... 113

4.5.1 Effect of CO2 concentration before the first stage ...... 115

4.5.2 Effect of CO2/N2 selectivity ...... 116

4.5.3 Effect of CO2 permeance ...... 118 4.5.4 Vacuum pump efficiency ...... 120 4.5.5 Effect of feed pressure ...... 120 4.5.6 Effect of membrane price on cost vs. feed pressure ...... 121 4.5.7 Comparison with literature ...... 122 4.6 Conclusions ...... 124 Acknowledgements ...... 125

CHAPTER 5 ...... 139 DEPOSITION OF ZEOLITE-BASED PARTICULATE LAYERS ...... 139 ON POLYMER SUPPORTS FOR CO2 CAPTURE ...... 139

5.1 Summary ...... 139 5.2 Introduction ...... 140 5.3 Background and rationale ...... 142 5.3.1 Zeolite Y as membrane material ...... 142 5.3.2 Zeolite membrane synthesis ...... 144 5.3.3 Seed layer deposition ...... 145 5.4 Experimental ...... 149 5.4.1 Materials ...... 149 5.4.2 Lab-scale coating ...... 150 5.4.3 Imaging by scanning electron microscopy ...... 152 5.4.4 Transport characterization ...... 152 5.5 Results and discussion ...... 153 5.5.1 Identification of appropriate polymer supports...... 153 5.5.2 Seed layer deposition by vacuum dip-coating ...... 155 5.5.3 Transport measurements ...... 157 5.6 Conclusions ...... 158 Acknowledgements ...... 159

CHAPTER 6 ...... 178 INORGANIC (ZEOLITE)/POLYMER MULTILAYER COMPOSITE STRUCTURES AS SUPPORTS FOR CARBON CAPTURE MEMBRANES ...... 178

6.1 Summary ...... 178 6.2 Introduction and rationale ...... 179 6.2.1 Supports ...... 179 6.2.1.1 Gas transport through porous materials……………………………...180 6.2.1.2 Effect of infiltration/penetration……………………………………..181 6.2.1.3 Pore size vs. surface porosity for polymer supports…………………182 6.2.2 Amine-based selective layer ...... 183 6.3 Experimental ...... 186 6.3.1 Materials ...... 186 xii

6.3.2 Membrane preparation ...... 187 6.3.3 Transport characterization ...... 188 6.4 Results and discussion ...... 189 6.4.1 Membrane thickness estimation ...... 190 6.4.2 Membranes with AIBA-K and KOH ...... 190 6.4.3 Membranes with TETA and KOH ...... 193 6.4.4 Membranes with lithium and potassium salts of glycine and KOH ...... 195 6.4.5 Effect of substrate………………………………………………………196 6.5 Conclusions ...... 198 Acknowledgements ...... 200

CHAPTER 7 ...... 214 SUMMARY AND FUTURE WORK ...... 214

7.1 Summary ...... 214 7.1.1 Process modeling and cost studies ...... 214

7.1.2 Experimental work on CO2-selective membranes ...... 215 7.2 Future work ...... 216 7.2.1 Process modeling and cost studies ...... 216

7.2.2 Experimental work on CO2-selective membranes ...... 217

APPENDIX A ...... 223 APPENDICES TO CHAPTER 4 ...... 223

A.1 Cost metrics ...... 224 A.2 Compressor capital cost estimation ...... 224 A.3 Make-up power unit cost estimation ...... 225 A.4 Auxiliary power estimation...... 226 A.5 Comparison of cost model with the DOE cost estimation technique ...... 226 A.6 Steps in cost computation ...... 227

BIBLIOGRAPHY ...... 230

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List of Tables

Table 2.1. Data used for model validation, reported earlier by Zou et al. *Membrane was placed between the two channels. So, in this case, permeation took place only through one side of the channel. ** These values were obtained from experimental data reported in previous work...... 39

Table 2.2. Base-case parameters and assumptions. *1 mil = 25.4 µm...... 40

Table 2.3. List of physical properties and other constants used in the simulations. The heat of reaction and specific heats were incorporated in the model as a function of temperature. For the gas mixture, the pure component properties were volume-averaged. All the other constants were evaluated at 393.15 K and 1 atm...... 41

Table 2.4. Hydrogen recovery and CO exit concentrations at different mesh sizes for both the contercurrent and crossflow modes. Feed pressure was set at 1.5 atm with all other parameters same as those given for the base-case in Table 2.2...... 42

Table 2.5. Pressure drops on feed and sweep sides for different flow modes. a) Countercurrent mode and b) Crossflow mode...... 43

Table 3.1. Transport characterization of lab-scale membranes with composition 46.2 % crosslinked PVA, 17.5% KOH, 26.5% AIBA-K and 9.8% PAA using the CO2-N2 gas mixture. All membranes were cured in the oven at 120 °C for six hours after overnight drying in the hood. Only the last membrane was cured immediately in the oven for 20 minutes. *The selectivity is the ratio of log-mean permeances...... 85

Table 3.2. Transport characterization of pilot-scale membranes with TETA using a CO2- H2-N2 gas mixture. All the runs had about 8 – 9 % TETA in their final membranes. Run #3: 33% crosslinked-PVA, 13% KOH, 22% AIBA-K, 22% Lupamin® and 3% APTEOS. Run #4: 33% crosslinked-PVA, 13% KOH, 22% AIBA-K, 21% Lupamin® and 3% APTEOS. Run # 30: 29% crosslinked-PVA, 14% KOH, 26% AIBA-K, 23% Lupamin®. Run #32: 34% crosslinked-PVA, 13% KOH, 27% AIBA-K, 17% Lupamin®. *Test gas $ contained no H2S. Measured using CO2-N2 gas mixture and in the rectangular cell………………………………………………………………………………….. ……86

Table 3.3. Transport characterization of pilot-scale membranes with EDA using a CO2- H2-N2 gas mixture. All the runs had about 8 – 9 % EDA in their final membranes. Run #40: 28% crosslinked-PVA, 18% KOH, 22% AIBA-K, 21% Lupamin® and 3% APTEOS. Run #54: 31% crosslinked-PVA, 17% KOH, 23% AIBA-K, 21% Lupamin® xiv and 3% APTEOS. Membrane #L-5: 33% crosslinked-PVA, 12% KOH, 23.5% AIBA-K, 23% Lupamin®. Membrane #L-6: 26% crosslinked-PVA, 18% KOH, 24.5% AIBA-K, ® * 23.5% Lupamin . Measured in the rectangular cell and N2 peak too small to calculate the selectivity...... 87

Table 3.4. Thicknesses and lengths of membranes fabricated using the TFC assembly and sent for spiral-wound module fabrication. The membrane composition was kept the same in all these runs. The membranes had about 30 – 31% crosslinked PVA, 16.6 – 17% KOH, 22.5 – 23% AIBA-K, 20 – 21% Lupamine, 8 – 9% EDA and 0 – 2.5% APTEOS. APTEOS was added in the casting solution to reduce frothing if observed...... 88

Table 4.1. Fixed parameters in the cost calculation.*This is the composition at the exit of the desulfurization unit. Component molar flow rates of O2 and SO2 were assumed to remain constant along the length of the membrane module...... 126

Table 4.2. Methodology to calculate economic parameters for the process. 1 US gallon = 3.785 liters. This unit make-up power cost was evaluated using numbers from Reference 5 as explained in Appendix A.3...... 127

Table 4.3. Effect of CO2 concentration before the first stage on overall costs for a CO2 permeance of 3000 GPU, pf of 1 bar and ps of 0.2 bar...... 128

Table 4.4. Comparison of current work with that by Merkel et al...... 129

Table 5.1. Surface morphology of the different supports used for zeolite deposition studied in this work. These numbers were obtained through analysis of SEM images shown in Figures 5.4 (a) and 5.6… ...... 161

Table 6.1. Membranes with AIBA-K/TETA/KOH as the mobile carrier. All were dried by the same method: 10 minutes of convective air drying at 120 °C. Only membrane 3 dried at 120 °C for one hr without forced convection. Expected thickness for these membranes is <1 μm. Notation: „P‟: Crosslinked PVA, „K‟: KOH, „A‟: AIBA-K, „T‟ TETA, „L‟: Lupamine, „Gly-L‟: Lithium glycinate, „Gly-K‟: Potassium glycinate and „KS‟: Potassium sulfite...... 201

Table 6.2. Membranes with TETA/KOH as the mobile carriers.All were prepared on the ZY-40 substrate...... 202

Table 6.3. Membranes with lithium glycinate/KOH as the mobile carriers. All were prepared on the ZY-40 substrate. *Only this membrane in this table was tested with a CO2-N2 mixture...... 203

Table 6.4. Membranes with potassium glycinate and KOH as the mobile carriers. All were tested with a CO2-N2 mixture. All were prepared on the ZY-40 substrate. Curing time was kept the same at 90 minutes...... 204 xv

Table 6.5. Comparison between potassium glycinate, AIBA-K and lupamin®. All were tested with a CO2-N2 mixture. All were prepared on the ZY-40 substrate. Curing time was kept the same at 90 minutes...... 205

Table 6.6. Comparison between different supports with respect to their CO2 and water transport. All the results have been already mentioned once in Tables 6.1 to 6.5...... 206

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List of Figures

Figure 1.1. CO2-selective membranes for post- and pre-combustion carbon capture...... 8

Figure 1.2. CO2 (H2S)-selective membrane processes for high-purity H2 production (adapted from References 11 and 12): (a) CO2 (H2S)-selective membrane + low temperature WGS reactor, (b) CO2 (H2S)-selective membrane + low temperature WGS membrane reactor...... 9

Figure 2.1. Spiral wound module configurations. (a) Without sweep gas (reprinted with permission from MTR, Inc.), (b) Countercurrent flow with sweep, and (c) Crossflow with sweep. Both (b) and (c) reprinted from Reference 36...... 44

Figure 2.2. Schematic of a spiral-wound membrane reactor. (a) Countercurrent spiral- wound membrane reactor housing the WGS catalyst on the feed side, (b) Countercurrent mode, and (c) Crossflow mode...... 45

Figure 2.3. Comparison of model predictions and experimental data reported by Zou et al. The solid curve is predicted by the model...... 46

Figure 2.4. CO and CO2 concentration profiles (dry basis) along the length of the membrane reactor...... 47

Figure 2.5. Concentration profiles. Top: CO and Bottom: CO2 concentration (dry basis) on the feed side for the crossflow mode...... 48

Figure 2.6. Feed and sweep side temperature profiles for different flow configurations. Only the first one third of the reactor length is shown in this Figure. The profiles remain flat for the remainder of the reactor...... 49

Figure 2.7. Feed side temperature profiles for the countercurrent mode with three different overall heat transfer coefficients...... 50

Figure 2.8. Feed side temperature profiles for the countercurrent mode with three different sweep-to-feed ratios. Only the first one fifth of the reactor length is shown in the Figure. The profiles remain fairly flat and predictable for the remainder of the reactor...... 51

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Figure 2.9. Feed and sweep side temperature profiles for the crossflow configuration. Top: feed and Bottom: sweep...... 52

Figure 2.10. Parametric sensitivity for the crossflow configuration. Top: U at 70 times lower than the base case but at the same γ of 1.25; Bottom: γ = 2 but at the same U of 180 W/m2/K...... 53

Figure 2.11. Effects of feed pressure on membrane area and hydrogen recovery in reaching <10 ppm CO for countercurrent and crossflow configurations...... 54

Figure 2.12. Effects of feed pressure on membrane area and hydrogen recovery in reaching <10 ppm CO for countercurrent and crossflow configurations. Feed gas composition used was 1% CO, 4% H2O, 7% CO2, 43% H2 and 45% N2...... 55

Figure 2.13. Effects of sweep-to-feed ratio on membrane area and hydrogen recovery in reaching <10 ppm CO for countercurrent and crossflow configurations...... 56

Figure 2.14. Effects of steam/CO ratio on membrane area and hydrogen recovery in reaching <10 ppm CO for countercurrent and crossflow configurations...... 57

Figure 2.15. Effects of membrane permeance on membrane area and hydrogen recovery in reaching <10 ppm CO for the countercurrent configuration under the same reaction kinetics of the base case...... 58

Figure 2.16. Effects of reaction kinetics on membrane area and hydrogen recovery in reaching <10 ppm CO for the countercurrent configuration under the same membrane permeance of the base case...... 59

Figure 3.1. Mechanisms for separation through membranes ...... 89

Figure 3.2. Chemical structures of salts of some amino acids as mobile carriers and polyamines as fixed carriers...... 90

Figure 3.3. (a) Crosslinking of PVA with glutaraldehyde, (b) Side reaction of polyglutaraldehyde formation under the same conditions...... 91

Figure 3.4. Pilot-scale membrane fabrication machines. Top: Schematic of the coating machine. Bottom left: Actual TFC assembly in operation and Bottom right: Schematic of TFC assembly...... 92

Figure 3.5. Casting trough region of the thin film casting assembly. (a) Top view and (b) Front view...... 93

Figure 3.6. Gas-permeation set-up and the small rectangular cell ...... 94 xviii

Figure 3.7. 14-inch amine-based flat sheet polymer membrane fabricated using the TFC assembly...... 95

Figure 3.8. Effect of temperature and pressure on CO2 permeability for Run #47. For this, a CO2-N2 mixture gas was used which had an unusual composition (determined based on GC analysis) of 30.5% CO2 and rest N2. To ensure comparison with results obtained using other gases, the dry gas flow rate was reduced to 40 cc/min and the base feed pressure was reduced to about 1.5 atm. The base temperature was 106 °C with water flow rates kept at 0.03 g/min on both feed and sweep sides...... 96

Figure 3.9. Effect of membrane thickness on CO2 permeance. All the measurements carried out in the rectangular cell and reported in Tables 3.1 to 3.3...... 97

Figure 4.1. Membrane process using combustion air as sweep (feed compressor/blower, pumps and heat exchangers are not shown). The numbers in parentheses indicate streams...... 130

Figure 4.2. Schematic of cost-sensitivity calculation procedure...... 131

Figure 4.3. The variation of membrane area with CO2 concentration before the first stage for a CO2 permeance of 3000 GPU, pf = 1 bar and ps = 0.2 bar. This plot corresponds to the data shown in Table 4.3...... 132

Figure 4.4. The effects of CO2/N2 selectivity on energy consumption and annualized non- membrane cost for XCO2 = 22.5%. This figure also implies that energy consumption is independent of the CO2 permeance. At a CO2/N2 selectivity of about 160 and pf = 1 bar, pf/ps = 5...... 133

Figure 4.5. The effects of CO2/N2 selectivity on membrane area and annualized membrane cost for XCO2 = 22.5%. The annualized membrane cost shown on the secondary y-axis corresponds to a CO2 permeance of 3000 GPU and pf = 1 bar...... 134

Figure 4.6. The effect of CO2/N2 selectivity on COE increase for a pf = 1 bar and CO2 permeance of 3000 GPU at XCO2 = 20.0% and XCO2 = 22.5%. At 22.5% CO2, the effect is shown at two different membrane element prices. At 20.0% CO2, the selectivities shown on the graph, 100, 136, 275, 300, 400, 500 and 600, correspond to pf/ps of 20, 8.6, 5, 4.8, 4.4, 4.2 and 4.1, respectively. At the same pressure ratio, the selectivity required is higher for 20.0% CO2...... 135

Figure 4.7. The effects of CO2 permeance on overall costs for XCO2 = 22.5% at a CO2/N2 selectivity of 163, pf = 1 bar and ps = 0.2 bar...... 136

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Figure 4.8. The effects of feed pressure on overall costs for XCO2 = 22.5%, a CO2 2 permeance of 3000 GPU, ps = 0.2 bar and the membrane module price at $2.5/ft ...... 137

Figure 4.9. The effect of feed pressure on COE increase at three different membrane element prices for XCO2 = 22.5%, ps = 0.2 bar and a CO2 permeance of 3000 GPU. For the element prices of $2/ft2, $6/ft2, and $10/ft2, the membrane module prices were $2.5/ft2, $6.5/ft2, and $10.5/ft2, respectively...... 138

Figure 5.1. Faujasite (FAU) (zeolite X or Y) cage structure...... 162

Figure 5.2. Zeolite Y seed layer top surface in Reference 114...... 163

Figure 5.3. Schematic of the vacuum-assisted dip-coating set-up...... 164

Figure 5.4. Zeolite Y dip-coated (0.5 wt% dispersion in water,~200 nm particles) onto NL PSf support. (a) Bare NL PSf support, (b) With zeolite coating on NL PSf, and (c) Bare TriSep PSf support...... 165

Figure 5.5. Zeolite Y dip-coated (0.5 wt% dispersion in water, ~200 nm particles) onto Sterlitech PES support……………………………………………………………….....166

Figure 5.6. Commercial polyethersulfone supports used for zeolite Y coating ...... 167

Figure 5.7. Zeolite-Y vacuum dip-coated (0.5 wt% dispersion in water, ~200 nm particles) onto Sterlitech PES support. (left, Uncoated; right, coated) ...... 168

Figure 5.8. Zeolite-Y vacuum dip-coated (0.5 wt% dispersion in water, ~200 nm particles) onto Sterlitech PES support. (left, top view, SEM image; right, cross-section, FIB-SEM image)...... 169

Figure 5.9. Optical microscopic image of the Zeolite Y vacuum dip-coated (0.5 wt% dispersion in water, ~200 nm particles) onto Millipore PES 1000 kDa support...... 170

Figure 5.10. Zeolite (0.5 wt% dispersion in water, ~200 nm particles) vacuum dip-coated on NL PSf support...... 171

Figure 5.11. Optical microscopic image of zeolite Y vacuum dip-coated (0.58 wt% dispersion in water, ~40 nm particles) onto Millipore PES 1000 kDa support………...172

Figure 5.12. Optical microscopic image of zeolite Y vacuum dip-coated (0.19 wt% dispersion in water, ~40 nm particles) onto Millipore PES 1000 kDa support……. …..173

Figure 5.13. Optical microscopic image of zeolite Y vacuum dip-coated (0.19 wt% dispersion in water, ~40 nm particles) onto Millipore PES 300 kDa support………….174

Figure 5.14. Zeolite Y vacuum dip-coated (0.19 wt% dispersion in water, ~40 nm particles) onto Millipore supports. (top, on Millipore 1000 kDa; bottom, on Millipore 300 kDa)……………………………………………………………………………………..175

Figure 5.15. Zeolite Y vacuum dip-coated (0.1 wt% dispersion in water, ~40 nm particles) onto Millipore 300 kDa support: Top Left: Zeolite layer under lower magnification, Top Right: Zeolite layer under higher magnification, Bottom: Cross- section……………………………………………………………………………… …..176

Figure 5.16. Transport characterization of PDMS-coated zeolite seed layers and PDMS- coated polymer supports...... 177

Figure 6.1. Schematic of the transport mechanism through a porous substrate (Adapted from Reference 141) ...... 207

Figure 6.2. Schematic of a conventional polymer support...... 208

Figure 6.3. Relation between the gap setting and the measured thickness normalized to the casting solution concentration ...... 209

Figure 6.4. Initial membrane stability (no SO2). Membrane 2 in Table 6.3...... 210

Figure 6.5. Initial membrane stability (<1 ppm SO2). Membrane 3 in Table 6.3...... 211

Figure 6.6. Initial membrane stability and performance recovery (about 5 ppm SO2). Membrane 4 in Table 6.3...... 212

Figure 6.7. Initial membrane stability and performance recovery (about 5 ppm SO2). Membrane 3 in Table 6.4...... 213

Figure 7.1. Proposed continuous vacuum dip-coating set-up ...... 222

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List of Notations a ratio of the total surface area to the volume of bed (cm-1) ai adiabatic index (ratio of specific heat at constant pressure to that at constant

volume)

Cp specific heat at constant pressure, J/mol/K d diameter of the hollow fiber, cm dp diameter of pore or capillary, nm

D characteristic length (cm)

Dp mean catalyst particle diameter (cm)

Ec compressor/blower/vacuum pump power consumption, kW

Ep pump power consumption, kW f friction factor (dimensionless) h heat transfer coefficient (W/cm2.s) ht channel height or spacer thickness, (mil, 1 mil = 25.4 µm)

H partial molar enthalpy of component, J/mol

J steady-state flux, mole/(m2·s) k fluid thermal conductivity (W/cm/s) ke effective thermal conductivity of the catalyst bed (W/cm/s)

K permeability of the porous media, m2

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KT equilibrium constant of the reaction (dimensionless)

L length of a spiral-wound element (cm) lm membrane selective layer thickness (µm) ls total thickness of the membrane support (including the porous sub-layer,

nonwoven fabric and any additional layers) (µm) n molar flow rate, mole/s

Nu Nusselt number (dimensionless)

Pr Prandtl number (Cpµ/k)

P1 inlet pressure to the compressor, bar

P2 outlet or downstream pressure, bar

-6 3 2 P mixed-gas permeance, GPU (1 GPU = 10 cm (STP)/(cm ●s●cm Hg); 3000 GPU

-6 2 -1 2 = 10 mole/(m ●s●Pa) = 10 mole/(m ●s●bar)).

-6 3 Pe mixed-gas permeability, such that P = Pe/lm, Barrer (1 Barrer = 10 cm (STP)-

2 cm /(cm ●s●cm Hg)). For a 1 µm thick membrane and a permeability of 1000

Barrers, the permeance is 1000 GPU.

Pr pressure in the slip casting process, bar

Ps capillary suction pressure, bar p pressure, bar

Δp the design head of the pump, bar

Q deposition rate or flux of the liquid through the porous media, m/s

Qc gas molar flow rate to the compressor/blower/vacuum pump, mole/s

xxiii

3 Qp liquid volumetric flow rate, m /hr

R universal gas constant, 8.314 J/mol/K (82.1 cm3 atm/mol/K)

Re Reynolds number (dimensionless) r volumetric rate of reaction (mol/cm3/s)

T absolute temperature, K

ΔT temperature difference between feed and sweep sides, K

U overall heat transfer coefficient, W/cm2/K

W width of a spiral-wound element (cm)

X mole fraction on the feed side

Y mole fraction on the permeate or sweep side x position variable along the length of the spiral-wound element (cm) y position variable along the width of the spiral-wound element (cm) z position variable along the height of the spiral-wound feed or permeate channel in

Chapter 2 / position variable along the hollow fiber length in Chapter 4/position

variable in the direction of liquid flow in Chapter 5, cm

Zave average compressibility of the gas between the inlet and outlet conditions of the

compressor

Greek letters

α membrane selectivity

ηc isentropic efficiency of compression

ηp efficiency of pump

porosity of the catalyst bed

xxiv

m porosity of the membrane support

εs surface or skin layer porosity

γ molar sweep-to-feed flow rate ratio (wet basis)

µ fluid viscosity / viscosity of the coating dispersion in Chapter 5, Pa-s

ρ fluid density (g/cc)

ρb catalyst bulk density (g/cc)

σ interfacial tension between the substrate material and the coating liquid, N/m

stoichiometric coefficient

0 superficial gas velocity (cm/s)

velocity of gas at a given z through the spiral-wound feed/ permeate channel

(cm/s)

τ tortuosity (ratio of the total diffusion path length in a layer to its apparent

thickness)

Subscripts

0 initial cat catalyst material f feed side i, j species lm log-mean mx mixed s sweep side

Acronyms

xxv

COE cost of electricity, $/kWh

DOE Department of Energy

GHG greenhouse gas

MC total membrane module cost

MuPC make-up power cost

SAC separation and compression

SOTA state-of-the-art

TPI total plant investment

VOM annual variable operating and maintenance cost

xxvi

CHAPTER 1

INTRODUCTION

1.1 Overview

The average carbon dioxide level in the earth‟s atmosphere has increased from

280 ppm in the pre-industrial period to 379 ppm in 2005.1 Recent concentration has been

2 measured to be close to 400 ppm. The increase in CO2 level is widely accepted as the biggest contributor to increasing global temperatures.1,3 And the latest report of the

Intergovernmental Panel on Climate Change clearly attributes the major cause of CO2 increase to anthropogenic fossil fuel use.1

CO2 capture from fuel and flue gases is therefore believed to be the most important method to combat climate change. In this context, there are three technically plausible strategies: post-combustion capture (PCC), oxy-combustion, and pre-

4 combustion capture (PrCC). In PCC, CO2 has to be separated mainly from N2, the major diluent in the air used for combustion of coal or natural gas, the two most commonly used fuels in thermal power plants. Other and minor components include water vapor, O2, SO2 and NOx. In oxycombustion, by using O2 instead of air for combustion, an almost pure stream of CO2 can be obtained for sequestration. The only significant separation challenge exists in producing the pure O2 before fuel combustion. In another approach to 1 produce electricity, instead of directly burning fossil fuels or biomass, they can be gasified into a cleaner gaseous fuel syngas (CO + H2), which after appropriate purification can be used to produce electricity via gas turbines or fuel cells. To capture

CO2 before deriving energy and/or produce pure H2 as a preferred fuel or chemical feedstock, the syngas can be subjected to a water gas shift (WGS) reaction (CO + Steam

CO2 + H2). In pre-combustion capture (PrCC), CO2 has to be separated from H2.

Other and minor components include water vapor, H2S, and trace amounts of Ar, N2, NH3

5 and CH4.

Membrane separation, adsorption, and solvent absorption are the three main processes studied for both PCC and PrCC. Being the most well-developed of the three, solvent absorption has been analyzed in-depth by the Department of Energy (DOE).5 For

PCC using the state-of-the-art (SOTA) monoethanolamine process, the cost of electricity

(COE) increase in a typical coal-based power plant is predicted to be about 85%. For

PrCC in a coal-based integrated gasification combined cycle (IGCC) power plant, the

Selexol-based physical solvent system is expected to increase the COE by about 39%.

On the other hand, the economic targets set by DOE for the practical integration of CO2 capture, compression and sequestration are 35% and 10%, respectively, for the conventional and IGCC power plants with 90% CO2 recovery at a CO2 purity of at least

95%.5,6 It is obvious that the SOTA absorption processes are about two to four times more expensive than the set targets. This also represents an opportunity for new processes to emerge as sustainable CO2 capture technologies. Membranes hold great potential for CO2 capture due to numerous advantages such as lower energy consumption

2 compared to other processes, operational simplicity with no handling of steam and condensed phases, lower water consumption, compactness, and ease of maintenance due to absence of moving parts. Figure 1.1 depicts both PCC and PrCC using CO2-selective membranes. Both CO2- and H2-selective membranes have been shown to be promising

7,8 for PrCC. Some of the important advantages of CO2-selective membranes for PrCC are summarized below.

1. Along with H2, residual CO and N2 in the syngas can be separated from CO2. This

can help to reach higher CO2 purity in the stream to be sequestered.

2. Recovery target of 90% CO2 is somewhat arbitrary and is more susceptible to change

than the purity target of at least 95%. For a lower CO2 recovery requirement, the

amount of CO in the fuel stream will be higher due to a lower conversion in the WGS

reactor. To tackle this, an additional combustion step will be needed after CO2

capture for H2-selective membranes. Since CO is retained by the fuel stream for

CO2-selective membranes, they can provide more flexibility on CO2 recovery or CO

conversion target for the WGS reactor.

3. Applying the same rationale to N2, it can easily be concluded that they also provide

greater flexibility on the purity of O2 obtained from the air separation unit for the

gasification. H2-selective membranes cannot take too much nitrogen since it will

have to be separated from CO2 in an additional step before the capture. This

flexibility can also reduce the energy consumption of the air separation unit.

4. There is a greater scope to increase the reverse gas CO2/H2 selectivity by using

facilitated transport membranes since they are not limited by selectivity/permeability

trade-off characteristic of polymer membranes. Palladium membranes can achieve

infinite H2/other gas selectivities but on the other hand can easily be poisoned by the

sulfur compounds in the syngas.

Depending upon the end goal, the H2 purity and impurity constraints will be decided in a pre-combustion scenario. Energy production via gas turbine by itself does not impose a stringent H2 purity requirement. But H2 is an important chemical used for hydrogenation and hydrotreating in refineries and chemical plants and production of ammonia, methanol, etc. Also, with greater emphasis on proton-exchange membrane

(PEM) fuel cells for clean and efficient energy generation, the demand for ultra-high-

9,10 purity (<10 − 100 ppm CO, <10 − 100 ppb H2S) H2 can grow further. PEM fuel cells can be especially advantageous in on-board reforming for transportation and small scale off-shore power generation.

Industrially, high purity H2 is generally produced using pressure swing adsorption or amine-scrubbing of CO2 and H2S. Both these processes suffer from higher energy consumption due to sorbent regeneration. Additionally, for the former, the hydrogen recovery is generally less than 90%. Also, when producing pure hydrogen is of a high priority as in the case of electricity production by PEM fuel cells, retaining hydrogen at high pressure is energetically favorable and using sweep gas (e.g., air) to provide the driving force for a H2-selective membrane is not an option. It should also be remembered that industrially, the WGS reactor outlet CO concentration cannot be reduced to <0.5 –

1% due to equilibrium limitation.

In this regard, a highly CO2-selective membrane, while reducing the H2 losses during separation, can also aid in reaching almost 100% CO conversion in an otherwise equilibrium-dominated low-temperature WGS reactor. Steam or air can be used as sweep gas to provide driving force for the membrane separation step/steps. For CO removal, as shown in Figure 1.2, the membrane can be used either as a stand-alone separation unit before the low temperature WGS reaction or be integrated with WGS reaction in a CO2- selective membrane reactor. Both the WGS catalyst and the fuel cell platinum-based catalyst can also get poisoned by the H2S present in the syngas. H2S removal is therefore necessary before carrying out the low temperature WGS reaction. This can be easily integrated with CO2 removal if the membrane is tolerant towards H2S and can also separate H2S from other gases.

1.2 Outline and scope

The first part of this dissertation focuses on hydrogen purification for fuel cells.

Chapter 2 focuses specifically on the development of models necessary to predict the sizes of separators, reactors and membrane reactors shown in Figure 1.2. Prior work from the group concerned with hollow-fiber membrane modules has been extended and made more detailed for the more preferred spiral-wound membrane configuration. The detailed model took into account mass and energy balances, and also the pressure drop involved in both the feed and permeate channels. Chapter 2 deals specifically with the membrane reactor configuration which is the most complex of all the units shown in Figure 1.2. The same model can be simplified by either eliminating separation (for a WGS reactor) or

5 eliminating reaction (for a membrane separator) and applied to simpler units. Chapter 3 focuses on the lab-scale synthesis and more importantly, the scale-up of an amine-based polymer membrane for the above application at low pressures (1 – 3 bars) and >100 °C.

This work involved the installation and operation of a pilot thin-film casting (TFC) assembly to fabricate a 14-inch flat-sheet membrane. The membrane was provided as a deliverable for testing in an Office of Naval Research (ONR) project. The work also involved the transport characterization of the above membranes synthesized on both the lab- and pilot-scale.

The second part of the dissertation work focuses on the development of membrane processes for PCC. In Chapter 4, the feasibility of using CO2-selective membranes in a coal-fired power plant has been explored. For this, a detailed model for membrane processes (developed in Chapter 2) was combined with in-depth cost calculations to arrive at the sensitivity of capture costs to a host of membrane and process parameters.

Chapters 5 and 6 deal with the development of CO2-selective membranes on the lab-scale for this application. Motivated by the promise of inorganic/polymer multilayer composite structures for high performance membrane applications, the development of a deposition technique for thin inorganic particulate layers on porous polymeric supports is discussed in Chapter 5. Using images obtained by scanning electron and optical microscopy along with transport characterization, the success of the newly developed technique has been demonstrated. Also, support properties important for successful deposition have been identified. Using the zeolite/polymer multilayer porous structures as substrates, Chapter 6 focuses on the development of amine/zeolite multilayer composite membranes for the

6 above application. In Chapter 7, important conclusions from the work and recommendations for future work have been summarized.

Fuel

Combustor Air or O2

Stack Compression, CO2 Sequestration,

and Storage

Selective Membrane Selective

- 2 Fuel or Chemical H2, N2, CO feedstock CO

Fuel

Gasifier Steam, Air or O 2

Figure 1.1. CO2-selective membranes for post- and pre-combustion carbon capture.

CO , CO, 2 H2S-CO2 Membrane Module H2, N2, <100 ppb H2S H2S, H2O H2S, CO2

Sweep with CO 2 Sweep and H2S

WGS Membrane Reactor High purity CO2 H2 product

Sweep Sweep with CO2

Figure 1.2. CO2 (H2S)-selective membrane processes for high-purity H2 production

11,12 (adapted from References 11 and 12) : (a) CO2 (H2S)-selective membrane + low temperature WGS reactor, (b) CO2 (H2S)-selective membrane + low temperature WGS

membrane reactor.

CHAPTER 2

SPIRAL-WOUND WATER-GAS-SHIFT MEMBRANE REACTOR FOR

HYDROGEN PURIFICATION

2.1 Summary

Water-gas-shift (WGS) membrane reactor is a promising approach to purify hydrogen produced by hydrocarbon or biomass reforming to fuel cell grade (<10 ppm

CO). CO2-selective polymer membranes suitable for the above operation can potentially be fabricated into spiral-wound modules with catalyst packed on the feed side and sweep gas flowing on the permeate side. This chapter presents a detailed model based on both mass and enthalpy balances as well as pressure drop to study this intricate reactive separation system. The kinetics of the WGS reaction was incorporated using a published rate expression for the commercial CuO/ZnO/Al2O3 catalyst. The resulting 1-D

(cocurrent or countercurrent flow of feed and sweep streams) or 2-D (crossflow) system of differential equations were solved using COMSOL Multiphysics. The model was validated by comparing the predicted CO results with previously published experimental data for a lab-scale flat rectangular membrane reactor. The effects of the type of flow mode on concentration and temperature profiles within the membrane reactor were predicted. Also, a sensitivity study was carried out to quantify the effects of operating

10 parameters like feed pressure, sweep to feed flow rate ratio and steam/CO ratio on membrane area and hydrogen recovery. Results show that although the countercurrent flow mode is the most efficient in terms of CO reduction, the crossflow mode might provide a better trade-off between CO reduction and heat management. For the countercurrent mode, it was also shown that it is important to enhance both the CO2 permeance as well as the catalyst activity to reduce the membrane reactor size.

2.2 Introduction

Hydrogen is usually produced by steam or autothermal reforming of hydrocarbons, e.g., methane and naphtha; it may also be produced from coal and biomass. Along with H2, the syngas produced by these processes contains CO2 as the major diluent while CO and H2S as the major impurities. Industrially, absorption is typically employed to remove CO2 and H2S, while CO is converted by water-gas-shift

(WGS) reaction (CO + Steam CO2 + H2). This reaction is equilibrium limited due to which the outlet CO concentration cannot be reduced to <0.5 – 1%.13

In order to use H2 in platinum-based proton-exchange membrane fuel cells without poisoning the electrocatalyst, the CO needs to be reduced to <10 – 100 ppm depending upon the operating conditions and design of the fuel cell.9 Purifying hydrogen may also be important for its use as a raw material for production of chemicals. In our

14,12,11,15 previous work, we studied processes combining a highly CO2-selective membrane with the WGS reaction to tackle this separation. The separation and the reaction can be carried out simultaneously in a membrane reactor or in two consecutive

11 steps with the CO2 separation followed by CO removal. In both cases, the CO2 removal can shift the equilibrium towards the product side and assist in almost complete reduction/conversion of CO via the above reaction. Other approaches like pressure swing adsorption (PSA), CO methanation and CO preferential oxidation generally suffer from considerable H2 losses and/or require stringent CO2 separation by absorption upstream to the CO removal/conversion.9,16,17 Additionally, PSA along with absorption techniques are not suitable for transportation applications requiring a high power to weight ratio.9

Membrane reactors have been widely researched in the context of H2-selective membranes operating at relatively high temperatures (>350 °C or so).18,19,20,21,22 The separation of product, i.e., H2 or CO2, can effectively shift the equilibrium while maintaining relatively fast kinetics at high conversions. Important advantages of CO2- selective membrane reactor over the H2-selective option include recovering H2 at higher pressure (feed side), using air or steam sweep or vacuum as an option to provide driving force for separation, and reducing high temperature WGS catalyst deactivation by

14,18 14 CO2. In one of the previous papers by our group, Huang et al. presented a detailed model to study a CO2-selective hollow-fiber membrane reactor with sweep gas. The membrane considered was an amine containing polymer membrane based on facilitated transport.12,11,23,24 From the viewpoint of ease of membrane fabrication and catalyst housing, the thin-film composite membranes suitable for this application are likely to be scaled-up in the form of spiral-wound modules.24 Hence, it would be useful to model and simulate such a membrane reactor.

Various researchers have studied spiral-wound modules in relation to multicomponent gas separations. Approximate models including mass balances and permeate pressure drop have been proposed and validated in literature.25,26,27,28,29 In the case of pervaporation (feed is a liquid and permeate is in vapor phase), energy balances have also been included in more detailed models.30,31,32,33 However, there are no studies modeling a membrane reactor in the spiral-wound configuration. The main objective of this chapter is to present the development of a detailed model incorporating component mass and overall enthalpy balances as well as pressure drop (both feed and sweep sides) in a spiral-wound membrane reactor. After model validation using previously published experimental data for a flat-channel rectangular membrane reactor, we will present the effects of different flow patterns (cocurrent flow, countercurrent flow and crossflow between feed and sweep streams) on the concentration and temperature profiles within the reactor. Membrane area, hydrogen recovery and pressure drop are then quantified for a range of operating parameters while comparing the performance of the different flow modes.

It is important to note that H2S, a common impurity in the syngas can also be removed by the aforementioned amine containing membrane.10 In fact, Chapter 3, among other things, will also discuss the H2S transport characterization of these membranes.

Since the focus of this chapter was CO reduction/conversion (from <1% on mole basis to

<10 ppm), we assume that the syngas entering the membrane reactor is almost free of

H2S (<10 ppb) in order to protect the downstream catalysts.

2.3 Spiral-wound configuration with sweep gas

Spiral-wound modules were first developed for reverse osmosis and other water purification applications.24 They have also been used in acid gas separation from natural gas and hydrocarbon separations.34,35 The module for these applications (Figure 2.1a) has a central perforated tube for permeate collection and has no provision for introducing a sweep gas on the permeate side. Also, the feed and permeate streams flow perpendicular to each other in a crossflow pattern. However, patent literature shows useful designs to introduce sweep gas in different flow directions relative to the feed.36 Figures 2.1b and

2.1c show some of these designs. Thus, the spiral-wound configuration has sufficient flexibility to be fabricated as a membrane reactor with catalyst on the feed side (instead of the feed spacer) and sweep gas on the permeate side.

2.4 Modeling transport in a spiral-wound membrane reactor

This section will highlight the assumptions and the model equations describing the above system. It is useful to look at the schematic of the feed and permeate channels in a spiral-wound module shown in Figure 2.2 while considering the assumptions. For illustrative purposes, Figure 2.2a shows a schematic of the countercurrent mode with catalyst on the feed side. Figures 2.2b and 2.2c show the different types of configurations that can allow countercurrent (or cocurrent) and crossflow of feed and sweep streams, respectively.

The important assumptions involved in the model are:21,30,32,37

1. The membrane reactor operates at steady state in an adiabatic mode. In this context,

the term “adiabatic” applies to the entire membrane reactor (feed and permeate

channels). Each spiral-wound element is perfectly insulated from the surroundings.

2. The effect of curvature is ignored since the channel height is very small compared to

the radius of the module.

3. Continuum fluid transport model applies.

4. There is no mixing in the flow direction on both the feed and sweep sides. Fluid flow

is unidirectional (Feed: “x” and Sweep: “x” for countercurrent and cocurrent flows or

“y” for crossflow). Since both W and L >> ht (channel height or spacer thickness),

edge effects can be ignored.

5. For the crossflow configuration, the feed side variations in the y-direction and

permeate side variations in the x-direction are accounted through the dependence of

flux on the driving force which is a function of both the spatial coordinates. For the

1-D countercurrent or cocurrent configuration, these variations are negligible.

6. Feed-side and permeate-side variables are averaged in the z-direction.

7. Both fluid mechanical as well as thermal boundary layers are fully developed.

8. Both feed and permeate or sweep gases are ideal.

9. The Joule-Thompson effect due to permeate expansion from feed to sweep side can

be neglected.

10. The water-gas-shift catalyst remains active at temperatures as low as 120 °C.

11. Pressure drop can be expressed in terms of a semi-empirical correlation.

12. Heat transfer can be modeled using resistances-in-series model and convective heat

transfer correlations.

13. The membrane is based on facilitated transport as described in our previous

studies.12,11,23 Resistance to mass transfer is dominated by the membrane. External

concentration boundary layer resistances are negligible.

14. CO2 and H2 are the only permeating components. Their permeances are independent

of the partial pressures but depend on temperature. The permeation of water vapor

can be completely restricted by adjusting the water partial pressure on the sweep side

and consequently equalizing the driving force.

The assumptions 11 and 12 imply that a detailed fluid mechanical model to determine velocity profiles can be avoided. For assumption 14 to be legitimate, the maximum feed pressure in this work has been limited to 2 atm. The CO2 partial pressure for the gas composition given in Table 2.2 at this pressure (0.28 atm) is approximately the point at which carrier saturation sets in as shown by our previous work.23 At higher

CO2 partial pressures, the apparent CO2 permeability/permeance and the CO2/N2 selectivity can drop, lowering the hydrogen recovery. That regime has not been considered in this work.

Asssumption 14 also requires the use of a humidified sweep gas. For practical purposes, the use of atmospheric air as sweep gas will not only be an economical but also a convenient choice. In that case, some degree of humidification and heating will be required before the sweep gas enters the membrane module. For a fuel cell application, one option will be to recycle the cathode exhaust air as the sweep gas for the membrane

16 module. In that case, the air will already be humidified to saturation, typically at about

120 °C. Practically speaking, the water permeation can be minimized by this method but may not be completely restricted. If dry sweep gas is used, water permeation from feed to sweep side can reduce the CO conversion unfavorably by reducing the steam/CO ratio

(Section 2.6.3.3). To reduce this effect, the membrane reactor in that case might need to be split into multiple stages with reduced CO conversion in each stage and steam injection between successive stages.

The flux Ji of component i is defined as follows:

Ji P i p i (2.1)

where pi is the transmembrane partial pressure difference for component i. The permeance of component i can generally be written as Pe,i/lm, where Pe,i is the permeability of component i. The flux of any other permeating component j can be found using the selectivity, αi/j = Pi/Pj and Equation 2.1 applied for that component.

The basic expression for reaction rate, r, for the water-gas-shift reaction is taken as the one used by Huang et al.14 and originally developed by Keiski et al.38 for the commercial CuO/ZnO/Al2O3 catalyst in the presence of excess steam (Molar steam/CO >

2.6). The equation below was multiplied by a factor of 2 for the state-of-the-art catalyst to account for the subsequent improvements in the activity.39,40

npfco b f 5557 nnfH fco r exp 13.39 1 22 (2.2) n RT Tf K n n f f T fco fH2 O

The rate of consumption or production of component i can be written in terms of the above reaction rate and the component stoichiometric coefficient. 17

rrii (2.3)

where i = 1 for CO2 and H2 while it is “-1” for both CO and H2O. The equilibrium

41 constant KT is given below as originally obtained by Moe.

4577.8 KT exp 4.33 (2.4) Tf

It is useful to look at the crossflow mode for the development of equations. The equations will involve differentials relative to two spatial coordinates x and y. The equations for cocurrent and countercurrent flow can be easily derived by replacing y with x in the crossflow equations with appropriate changes in the signs of the flux terms.14,21,25

In addition, the velocity and pressure drop terms have to be modified appropriately to account for the differences in permeate channel cross-sectional area and flow distance, respectively.

2.4.1 Molar balances

Molar balances can be written for each component i as shown in Equations 2.5 and 2.6 for the feed and sweep sides, respectively.

dn fi Wh r2 WJ (2.5) dx tf i i

dn si 2LJ (2.6) dy i

In the above equations, the left-hand sides represent the change of component molar flow rate with respect to position in the feed and sweep sides, respectively. The right-hand sides include the permeation through the membrane whereas the right-hand side of Equation 2.5 also includes the reaction term. Feed side stream enters at x = 0 and 18 exits at x = L while the sweep stream enters at y = 0 and exits at y = W (Figures 2.2b and

2.2c). The factor of 2 is due to the presence of two membrane sheets per element in a spiral-wound module.

2.4.2 Enthalpy balances and heat transfer

The overall enthalpy balance for the feed side is written as:

d() nfi H fi 2WJHWUTT (i fi ) 2 ( f s ) dx ( 2. 7)

The above equation shows that the total enthalpy of the feed stream can change via two routes:

1. Due to the enthalpy carried by the permeating components from the feed side to the

sweep side.

2. Due to heat transfer between feed and sweep sides including the conductive heat

transfer through the membrane layer.

It is obvious that although the element is assumed to be adiabatic globally (from assumption (1)), both the feed and permeate streams can exchange heat with each other.

From Equation 2.4 and some mathematical manipulation, the above equation can be further simplified as shown below:14,42,43

dHfi dn fi (nfi ) ( H fi ) 2 W ( J i H fi ) 2 W U ( T f T s ) dx dx

dH (nfi ) HWhrWJ ( 2)2()2() WJH WUTT fidx fi tf i i i fi f s

dH (nfi ) HWhr () HWJ (2)2()2() WJH WUTT fidx fi tf i fi i i fi f s

dH (nfi ) Wh H r 2 W U ( T T ) fidx tf fi i f s

dH fi (n ) Wh H r 2 W U ( T T ) fidx tf fi i f s

We know that the heat of reaction is defined as follows:

( 2. 8) HHr fi i Thus,

dH fi (nfi ) Wh tf r H r 2 W U ( T f T s ) dx

With no phase change, dHfi C pfi dT f . So, the equation can be rewritten as:

(2.9) dTf Wh tf r H r 2 WU T

dx() nfi C p fi where ΔT = Tf – Ts. The left hand side of Equation 2.9 represents the change of

temperature with respect to position in the feed side. It can be noted that Hr is negative for the exothermic WGS reaction due to which the temperature on the feed side will increase due to the first term in the numerator of the right hand side.

The overall enthalpy balance for the sweep side can also be written and simplified.

d() n H si si 2L ( J H ) 2 LU ( T T ) dy i fi f s

dH (nsi ) 2 L J ( H H ) 2 LU ( T T ) sidy i fi si f s

The equation can be further simplified by noting dHsi C psi dT s and

HHCTTfi si psi() f s .

2 LUTLJCT 2 ( ) dTs i psi dy() n C si psi (2.10)

The additional term in Equation 2.10 compared to that in Equation 2.9 represents the difference in the energy carried by the permeate between leaving the feed side and entering the sweep side. The overall heat transfer coefficient U can be calculated by the standard resistances-in-series model for heat transport. Both, feed and sweep side boundary layer resistances as well as conduction through the membrane and support layers can be considered to obtain the total resistance.

For the sweep channel, the spacer has to be highly porous (>90%) to minimize the hydraulic resistance. This is possible since the spacer for gas separation is not required to enhance mass transfer in the gas phase. For the purpose of calculating the heat transfer coefficient on the sweep/permeate side, we assume that the channel is empty. The error caused by this assumption is expected to be small.44 The Nusselt number for this flow is

21 taken as the average between the “constant heat flux” and “constant wall temperature” cases.37

(7.541 8.235) hDss Nus (2.11) 2 ks where Ds, the characteristic length, is defined as:

4Flow area 4Lh Dhts 2 (2.12) sWetted Perimeter2 L ts

For the feed channel with catalyst, the catalyst can occupy more than 60% of the total volume due to which the heat transfer characteristics are expected to be significantly different from that of an empty channel. In this case, we have used the correlation given by Kaviany45 and used by Kim et al.46 for a parallel plate micro-WGS reactor.

hD Nu 2 (0.4Re1/2 0.2Re 2/3 ) Pr 0.4 ff (2.13) f Dpp D ke where

Df = 2htf. (2.14)

Dp is the mean catalyst particle diameter which is defined as follows:

6(1 ) D (2.15) p a where a is the wetted surface area of particles per unit bed volume. The effective thermal conductivity of the catalyst bed is defined below:

ke k f(1 ) k cat (2.16)

The Reynolds number is given as:

D Re p0 f f (2.17) Dp f (1 )

From the ideal gas law, 0 f , the superficial gas velocity on the feed side can be related to the total molar feed flow:

nff RT 0 f (2.18) pf Wh tf

The overall heat transfer coefficient, U, can then be found by adding the conductive as well as the convective resistances.

1 U (2.19) 11llms

hf k m(1 m ) k m m k s h s where km, the thermal conductivity of the selective layer material is assumed to be the same as that of the support material.14

2.4.3 Pressure drop (momentum balance)

The pressure drop is obtained by solving the momentum balance or the equation of motion. In the absence of external forces, the equation of motion can be simplified to the form shown in Equation 2.20 for a steady and unidirectional flow through an empty feed or permeate channel.30,37 Other assumptions include laminar Newtonian flow and that the viscous stresses are important only in the z-direction. Equation 2.20 shows the momentum balance for the permeate flow. Similar equation can be obtained for the feed flow by interchanging y with x.

dddp 2 s 0 (2.20) ssdy dy dz2

The first term on the left hand side of the equation represents the rate of change of bulk fluid momentum which is expected to be negligible for the low Reynolds number laminar flows encountered in a spiral-wound channel.30,37 The Equation 2.20 thus reduces to:

dp d 2 s dys dz2

In the above equation, the left hand side does not depend on z. It can be obtained by solving for in terms of z.

dp2 f 2 s s0 s (2.21) dy hts

A hts0 s s where the friction factor f , Reh , and A = 6 for an empty channel. Reh s

As for the feed side, 0s can be related to ns by the ideal gas law (similar to Equation

2.18).

For a spacer-filled channel, the constant A is larger owing to the greater hydraulic resistance. For open spacers such as those needed in the case of gas separations or the permeate channels of a pervaporation module, A is between 20 and 30.32,47 In this study, we assume A = 24 for the permeate spacer.32

For the feed side, the channel is packed with catalyst particles. For laminar flow through a packed bed of particles, the Blake-Kozeny equation (a special case of the

Ergun equation derived under negligible inertial flow37) gives an estimate of the pressure drop. 24

2 dp f f0 f (1 ) 150 23 (2.22) dx Dp

2.4.4 Boundary conditions and solution procedure

The Equations 2.5, 2.6, 2.9, 2.10, 2.21 and 2.22 constitute a system of partial differential equations similar to those discussed by Cao et al.32 and Hickey et al.30 for pervaporation applications. Except for the permeate pressure, ps, the boundary conditions are set by known conditions at the feed and sweep inlets. The permeate pressure is assumed to be 1 atm at the sweep outlet. The equations are non-dimensionalized with respect to known quantities like total molar flow rate at the feed entrance, the feed side inlet temperature and the feed inlet pressure. This system of equations was then solved by using the equation-based finite element method in COMSOL Multiphysics Version

3.4. The 2-D domain of the cross-flow mode was divided into 2000 mesh points with around 4000 triangular elements. The pre-defined element type was Lagrange quadratic.

The solution time was approximately 2 – 5 minutes on a computer with core i-7 3.4 GHz processor and 8 GB memory. The 1-D domain for the cocurrent and countercurrent modes was divided into around 2000 elements.

2.4.5 Membrane performance

The CO2-selective membrane considered in this study has been reported in our previous work. The data obtained by Zou and Ho23 was used to calculate the temperature dependence of both the CO2 permeance and CO2/H2 selectivity so that these quantities could be incorporated as a function of temperature in the membrane reactor model. The

25 equations were adjusted to agree with the best performance reported at 120oC.12 The final equations used in the model were as follows:

T 16.8 P 240 f (2.23) CO2 393.15

T 15.4 250 f CO2 / H 2 393.15 (2.24)

The above equations reduce to a CO2 permeance of 240 GPU and a CO2/H2 selectivity of

250 at 120 °C

2.5 Validation of model with experimental data

We validated the model above for the spiral-wound membrane reactor using data reported earlier by Zou et al.12 for a membrane reactor with flat rectangular feed and permeate channels. Since the effect of curvature in a spiral-wound module has been ignored, we believe that this is a valid comparison. Table 2.1 shows the operating conditions and other parameters used in those experiments including other input parameters.

Zou et al.12 operated the membrane reactor in an isothermal oven maintained at

150oC. Although the model discussed in Section 2.4 is developed for a globally adiabatic membrane reactor, it can be used to predict isothermal operation by imposing ΔHr = 0 in the model equations. This effectively eliminates the enthalpy balances from the model.

In the case shown in Table 2.1, the CO amount in the feed gas on wet basis is about

0.5%, and the sweep to feed ratio (wet basis) is 8. Under these conditions, the adiabatic

26 temperature rise is very small. As a result, there was no significant difference between the simulation results for the isothermal and the adiabatic models.

The model prediction for the variation of CO concentration at the retentate or feed outlet vs. the feed flow rate has been plotted in Figure 2.3. There seems to be reasonable agreement between the experimental data and the data predicted by the model, particularly in view of the CO detection limit of about 4 ppm by GC.

2.6 Sensitivity study

Table 2.2 shows the parameters of the base case chosen in this study, and Table

2.3 shows the values of different physical constants evaluated at the simulation conditions. In order to establish the mesh independence of the results reported in this chapter, Table 2.4 shows the H2 recovery and CO exit concentration for both the countercurrent and crossflow modes at two different mesh sizes.

The membrane considered for this application has shown excellent performance combined with good stability at 100 – 120 °C. Thus, the inlet temperatures of the feed and sweep gases were kept constant at 120 °C for all the simulations. Variations in the inlet temperatures have been reported before by Huang et al. for a hollow-fiber membrane reactor14,15 and will not be considered in the subsequent discussion. The composition of the gas mixture is typical of an autothermally reformed syngas after a low temperature WGS reaction step.

2.6.1 CO2 removal and CO conversion

Figure 2.4 shows the CO and CO2 concentration profiles in the feed channel for the countercurrent and cocurrent configurations. CO can be reduced to <10 ppm in the countercurrent mode while the cocurrent case can only reach about 480 ppm CO. In both modes, the CO2 and CO profiles seem to follow similar trends relative to each other. CO2 is reduced to about 400 ppm in the countercurrent mode while its profile flattens out at about 4.7% in the cocurrent mode. It is therefore clear that the efficiency of CO2 removal is crucial to shifting the WGS equilibrium towards high CO conversions. The inefficient use of driving force is characteristic of the cocurrent mode and has been studied before

19 for a membrane reactor in the case of inorganic H2-selective membranes. Although it is generally known that the countercurrent mode provides a more uniform driving force than the other modes, Figure 2.4 re-emphasizes its importance for a reactive separation system.

Figure 2.5 shows the CO and CO2 concentration profiles for the crossflow mode.

In this case, the concentrations vary in both the directions due to the dependence of the flux on both the feed and permeate side mole fractions (Equation 2.1). The variation in both the directions is more obvious in the case of CO2 profile. This is expected since the change in molar flow rate of CO2 depends directly on its flux. Along the length of the feed side, the CO2 concentration changes more rapidly near the sweep inlet at y = 0 (no

CO2 in the incoming sweep gas) and more slowly near the sweep outlet where the sweep gas is relatively richer in CO2. On the other hand, the CO molar flow rate change

28 depends indirectly on the CO2 flux through the shifting of the equilibrium for the WGS reaction. Thus, its profile is more one-dimensional (the change is mainly in x-direction).

Unlike the cocurrent mode, the CO (averaged in the y-direction) can reach <10 ppm at the outlet for the crossflow mode. The use of driving force is still not as efficient as in the countercurrent mode, which is evident from the larger membrane area requirements (discussed in Section 2.6.3.1).

2.6.2 Heat transfer and temperature profiles in the membrane reactor

The water-gas-shift reaction is moderately exothermic due to which the temperature along a packed bed reactor is expected to increase in the absence of any cooling. In case of a membrane reactor with sweep gas, the heat exchange with the sweep gas can alter this trend appreciably and lead to a complicated temperature profile.14,21,22 The temperature profiles within the reactor could be important both from the membrane performance as well as the catalyst activity point of view. Obviously, the temperature also affects the kinetics as well as the equilibrium of the reaction. Also, avoiding hot spots could be important to obtaining optimum reactor performance.

Figures 2.6 to 2.10 show the temperature profiles on both the feed and sweep sides for different flow configurations under certain conditions. For the countercurrent configuration, we see a peak in the temperature profile near the feed inlet. The temperature rise due to the heat of reaction is followed by a drop in temperature towards the feed outlet due to heat transfer from the feed to sweep side. The cocurrent flow pattern shows a different behavior. The feed side temperature increases and becomes

29 more stable along the membrane reactor much like the CO2 concentration profile shown in Figure 2.4.

A closer examination of Figure 2.6, particularly for the sweep side profiles, can reveal the reasons for these differences between the two modes. In the cocurrent mode, both the sweep and feed streams enter the membrane reactor at the same side. As the reaction proceeds along the length of the feed side, it heats up the feed stream as well as the sweep stream due to heat transfer along with the heat of reaction. Since the sweep stream gets heated up simultaneously, there is no subsequent cooling of the feed gas and the temperatures remain stable. But, for the countercurrent mode, the sweep gas takes away the heat from the feed side and is at its highest temperature near the feed inlet.

Near the feed inlet, CO concentration is relatively high due to which the rate of reaction and heat evolution are also high. This situation leads to a temperature peak near the feed inlet as shown in Figure 2.6.

At this point, it is helpful to note that for 1% CO concentration, the adiabatic temperature rise due to reaction is about 10oC or so. Due to permeation, the heat evolved is taken up by a progressively smaller stream in a membrane reactor. Due to this effect, the adiabatic temperature rise in a membrane reactor in the absence of any heat exchange between feed and sweep sides can go up further by 2 – 3oC.21 The difference between the peak temperature and inlet temperature on the feed side as shown in Figure 2.6 is well above this expected rise and is due to the heat-feedback phenomenon associated with the countercurrent configuration as discussed in the preceding paragraph. This behavior has been studied in depth in the case of simultaneously-cooled exothermic packed-bed

30 reactors and is generally accompanied by unfavorable outcomes such as steady state multiplicity and high parametric sensitivity.48,49

The heat feedback efficiency depends on the efficiency of heat transfer. Thus, it is useful to look at the effect of the overall heat transfer coefficient on the temperature profiles. This is shown in Figure 2.7 for arbitrarily reduced heat transfer coefficients. As

U reduces, the temperature jump reduces and the profile becomes more uniform along the length of the reactor. It is important to note, however that it might not be practically possible to attain such insulating conditions (between feed and sweep) in a membrane reactor/module. In the small channels of the spiral-wound element, heat transfer coefficients are comparatively higher than the shell-side of a hollow-fiber module,50 a commonly used configuration for the study of polymeric membrane separators and reactors. Huang et al.14 reported a temperature rise of about 15 – 20oC for 1% CO containing autothermally reformed syngas. The heat transfer for the shell side in that case was less than 4 W/m2/K.14

Recently, Adrover et al.21 studied these characteristics of countercurrent flow for an H2-selective palladium-based membrane reactor. In addition, they also looked at the effect of sweep flow rate on the temperature profiles inside the reactor. They concluded that higher sweep flow rates can reduce the temperature jump as well as the parametric sensitivity. The effect of sweep-to-feed ratio is shown in Figure 2.8. At higher sweep-to- feed ratios, we can clearly see that the temperature jump reduces considerably. This is mainly due to the resultant higher heat capacity of the sweep stream and the lower rise in sweep temperature.

The crossflow mode presents an interesting case. Although it is intuitive to expect that the temperature profile must be between that of the above two flow modes, the 2-D sweep and feed temperature profiles shown in Figure 2.9 show a maximum of about 134oC which is very close to the adiabatic temperature rise. The maxima is located near the sweep outlet which is expected since the average sweep temperature increases from y = 0 to y = W. The top and bottom diagrams of Figure 2.10 show the effects of U and γ on the feed side temperature profiles, respectively. As shown in Figure 2.10 (top and bottom), the maxima of the feed side temperature attained is close to that in Figure

2.9 for the base case (U = 180 W/m2/K) and therefore insensitive to the overall heat transfer coefficient or the sweep-to-feed ratio, which demonstrates the lower parametric sensitivity of the crossflow mode. At a higher sweep-to-feed ratio, the average temperatures reduce on both sides, which is due to the higher heat capacity of the sweep stream. The heat feedback seen in the countercurrent configuration cannot take place efficiently in the crossflow mode, which gives rise to more favorable temperature profiles like the cocurrent mode.

2.6.3 Effects of system parameters on membrane area, hydrogen recovery & pressure drop

Membrane area, hydrogen recovery and the pressure drop through the membrane reactor will dictate the capital as well as the operating costs associated with the above operation. It is useful to therefore look at the effects of important system/operating parameters on these quantities. Since it is not possible to reach very low levels of CO with the cocurrent flow mode at moderate feed pressures (1 – 4 atm in this study), we will

consider only the countercurrent and crossflow modes for the subsequent discussion. In

addition to base-case gas composition given in Table 2.2, a slightly different gas

composition with 1% CO, 4% H2O, 7% CO2, 43% H2 and 45% N2 was used to look at the

effects of feed pressures from 2 atm to 4 atm.

2.6.3.1 Effect of feed pressure

The effects of feed pressure on membrane area and H2 recovery are shown in

Figure 2.11 keeping all other quantities fixed at values shown in Table 2.2. The membrane area drops sharply at higher feed pressures. In a membrane reactor with a gas phase reaction, feed pressure affects both the reaction rate as well as the flux through the membrane. So, in general, the area is expected to reduce more than proportionately with increase in pressure.14,51 We see that the membrane area reduces from about 2050 m2 to

600 m2 for the countercurrent configuration as the feed pressure increases from 1 atm to 2 atm. In the same range, the effects of feed pressure for the crossflow configuration are even more drastic. The membrane area drops from around 5800 m2 to about 1070 m2 as the feed pressure increases from 1 atm to 2 atm. At higher feed pressures, the effect of sweep side concentration on mass transfer can be expected to reduce. Consequently, the crossflow and countercurrent configurations yield membrane areas closer to each other.

In order to see the effect of even higher feed pressures, a different gas composition was used in the simulations to avoid the regime of “carrier saturation” in the membrane. The CO2 was reduced from 14% to 7% while the nitrogen was increased from

38% to 45%. It can be seen from Figure 2.12 that the membrane area for this composition is approximately the same as for the base case at 2 atm. The membrane area reduces to

33 about 250 m2 and 340 m2, for the countercurrent and cross-flow configurations, respectively, at a feed pressure of 4 atm.

Hydrogen recovery increases at higher feed pressures. This can be attributed to the fact that H2 concentration in the feed gas is much higher than that of CO2 due to which the H2 flux is less sensitive to feed pressure. The hydrogen recovery for the countercurrent mode at 4 atm goes up close to 96 – 97% while that for the crossflow mode reaches about 95 – 96% (Figure 2.12).

These results show that higher feed pressures will not only make the membrane reactor smaller but also reduce the hydrogen losses. Additionally, higher pressure can reduce the volumetric flow rates and help the gasification system of a given size to achieve a higher productivity. But for a facilitated transport membrane, however, carrier saturation will set in at a certain CO2 partial pressure, above which the CO2/H2 selectivity will start dropping. Thus, there will be an optimum operating pressure for a given membrane composition.

2.6.3.2 Effect of sweep-to-feed ratio

The effects of increasing the sweep-to-feed ratio γ from 1.25 to 2 are shown in

Figure 2.13 for both the flow modes. Although the effects are similar to those of the feed

pressure, they are much less pronounced in this case. The membrane area drops by about

15% when the sweep-to-feed ratio increases from 1.25 to 2 for the countercurrent

configuration. For the crossflow mode, the drop is about 32% in the same range. This

ratio affects only the mass transfer rates through the membrane reactor. Typically, the

effects are therefore much weaker than those of feed pressure. The hydrogen recovery

34 also follows a similar trend as in the case of feed pressure due to the lower sensitivity of hydrogen flux to permeate dilution.

Table 2.5 shows the pressure drops on the feed and sweep sides for some of the cases discussed in Sections 2.6.3.1 and 2.6.3.2. In this study, the catalyst particle diameter and sweep side spacer thickness were chosen to limit the pressure drop on either side to a maximum of about 10% of the inlet fluid pressure. In most cases, as shown in

Table 2.5, the pressure drops were close to 5% or less. In general, as feed pressure increases, the flow per element increases due to reduced membrane area requirements

(increased productivity). But, the compression can also reduce volumetric flow rates on the feed side. For the sweep side however, there is no compression effect. This coupled with the lower sweep side pressure and larger volumetric flow means that the percentage pressure drop (on the permeate side) is more significant compared to the feed side. This is similar to the effects observed in pervaporation where the permeate vapor pressure drop is much more important than that on the feed side.47 Similar effects are observed for increase in sweep-to-feed flow rate ratio except in that case, there is no compression effect on the feed side and the sweep pressure drop is due to both an increase in productivity as well as the sweep-to-feed flow ratio.

The higher pressure drop on the sweep side for the crossflow mode relative to that of the countercurrent mode is caused by both the greater flow distance (W > L) as well as

the smaller flow cross-sectional area (L hts < W ) for the crossflow mode vs. the countercurrent mode.

2.6.3.3 Effect of steam-to-CO ratio

Steam-to-CO ratio is an important operating parameter in a WGS reactor which can be used to drive the equilibrium in the direction of CO conversion. The effects shown in Figure 2.14 seem similar to those of the sweep-to-feed ratio. Under the conditions of the base case, there seems to be little benefit in increasing the steam-to-CO ratio to more than 8 or so. Also, the crossflow mode seems to benefit more from the increase in this ratio.

2.6.3.4 Effects of reaction kinetics vs. membrane permeance

Figures 2.15 and 2.16 show the effects of reaction kinetics/catalyst activity and membrane permeance on membrane area and hydrogen recovery. With the fixed present kinetics (a value of “1” on the x-axis of Figure 2.15), the membrane area reduces significantly up to 2 times the membrane permeance of the base case, i.e., a CO2 permeance of 480 GPU. At the same time, the hydrogen recovery reduces since the membrane area drops at a lower rate than that of the increase in membrane permeance.

When the CO2 permeance is doubled, the H2 permeance is also doubled while keeping the same CO2/H2 selectivity. Thus, the hydrogen recovery reduces, and it reduces at a higher rate as the area drops at a lower rate than that of the increase in membrane permeance.

Similarly, as shown in Figure 2.16, at the base-case membrane permeance of 240

GPU, increasing the catalyst activity to 2 times the base-case value reduces the membrane area. This reduction is somewhat slower than the change caused by the increase in membrane permeance. Also, it is accompanied by an increase in hydrogen recovery due to the reduced membrane area to reach <10 ppm CO, resulting in the lower

36 hydrogen loss. These results also tend to show that increasing both the membrane permeance as well as the catalyst activity beyond the present base-case values is important to decrease the membrane area or the membrane reactor size drastically without reducing the hydrogen recovery.

2.7 Conclusions

1) A detailed model for a spiral-wound WGS membrane reactor was developed using

mass and enthalpy balances along with pressure drop equations and partly validated

by previous experimental data. Since the fundamental equations are the same as for

flat rectangular channels, the model is applicable even for other designs such as the

plate-and-frame type.

2) The model was used to predict membrane reactor performance and size along with

concentration and temperature profiles within the reactor for various flow modes.

The predictions agreed qualitatively with similar findings in literature.

3) The countercurrent configuration was the most efficient in terms of CO

reduction/conversion as expected from literature and previous studies. Cocurrent and

crossflow modes however offered better heat management potential through

relatively flat temperature profiles.

4) At about 4 atm, the membrane area for the crossflow mode was only about 35% more

than the countercurrent mode in order to reach <10 ppm CO (Figure 2.12). This

combined with the fact that the crossflow mode provides a more favorable

temperature profile makes it an interesting alternative especially at higher inlet CO

concentrations.

5) Under the present performances of the catalyst and membrane, both affect the

membrane reactor size. In order to decrease the size further without significantly

affecting the hydrogen recovery, it is important not only to obtain a more active

catalyst but also increase the CO2 permeance through the membrane.

6) It is fairly obvious that the same model can be simplified by assuming the reaction

term zero for a membrane separator or the flux terms zero for the WGS reactor. Also,

flux equations for the feed and permeate channels can be routinely added for

additional components such as H2S. Basically, the model can be easily applied to

entire processes such as those shown in Figure 1.2 or in Chapter 4.

Acknowledgments

The authors would like to thank the Office of Naval Research (N00014-11-C-0062) and the National Science Foundation for the financial support of this work. Part of this material is based upon work supported by the National Science Foundation under Grant

No. CBET 1033131 and IIP 1127812.

Table 2.1. Data used for model validation, reported earlier by Zou et al.12 * Membrane

was placed between the two channels. So, in this case, permeation took place only through one side of the channel. ** These values were obtained from experimental data

reported in previous work.12,23

Conditions/Fixed Parameters

Feed composition (dry basis) 1% CO, 17% CO2, 45% H2, 37% N2 Sweep gas Humidified argon Temperature (°C) 150 Feed pressure, Sweep pressure (atm) 2, 1 γ 7.86 % Steam in feed, % Steam in sweep 45, 93 Channel length (cm) 19.7 Channel width (cm) 17.4 Membrane area (cm2)* 342.7 Feed channel thickness (inch, cm) 3/32, 0.238 Sweep channel thickness (inch, cm) 1/4, 0.635 lm (µm) 53 ls (porous support + porous Teflon layer +filter paper) 200 (µm) Catalyst amount (g) 40 – 45

Assumptions for Model Prediction

** CO2 permeability (Barrers) 5000 ** CO2/H2 selectivity 160 No pressure drop

Table 2.2. Base-case parameters and assumptions. * 1 mil = 25.4 µm.

Parameter Value

Feed composition (wet basis) 1% CO, 4% H2O, 14% CO2, 43% H2, 38% N2 Sweep gas Humidified air nto (wet basis, mole/s) 1 Feed and sweep inlet temperature (°C) 120 Feed inlet pressure, Sweep outlet pressure 2, 1 (atm) γ 1.25 L (cm) 50.8 W (cm) 76.2 Membrane area in one element (cm2) 7742 * htf (mils) 20 h (mils) 9 ts lm (µm) 25 ls (µm) 140 A 24

Membrane Performance (120 °C )

CO2 permeability (Barrers) 6000 CO permeance (GPU) 2 240 CO2/H2 selectivity 250

Table 2.3. List of physical properties and other constants used in the simulations.14,52 The

heat of reaction and specific heats were incorporated in the model as a function of temperature. For the gas mixture, the pure component properties were volume-averaged.

All the other constants were evaluated at 393.15 K and 1 atm.

Property Value

ΔHr, at 298 K 41400 J/mol -4 kcat (W/cm/K) 40 × 10 -4 km (W/cm/K) 17 × 10 -4 kf (W/cm/K) 11.22 × 10 -4 ks (W/cm/K) 3.24 × 10 -5 µf (Pa-s) 1.67 × 10 -5 µs (Pa-s) 2.22 × 10

Cpf (J/kg/K) 1700 Cps (J/kg/K) 1080 3 ρf (kg/m ) 0.58 3 ρs (kg/m ) 0.87 0.4 0.75 m b 1.395 a 343 (for a 175 µm spherical particle)

Table 2.4. Hydrogen recovery and CO exit concentrations at different mesh sizes for both the countercurrent and crossflow modes. Feed pressure was set at 1.5 atm with all other

parameters same as those given for the base-case in Table 2.2.

Mesh Membrane Hydrogen CO exit type area (m2) recovery (%) concentration (ppm, dry) 1920 elements, 34569 920 95.2367 9.39 degrees of freedom Countercurrent 3840 elements, 920 95.2349 9.84 69129 degrees of freedom

978 elements, 18153 1860 90.5824 9.45 degrees of freedom Crossflow 3912 elements, 1860 90.5820 9.40 71505 degrees of freedom

Table 2.5. Pressure drops on feed and sweep sides for different flow modes. a)

Countercurrent mode and b) Crossflow mode.

p f (atm) ps (atm)

2 0.110 0.031 Effect of feed pressure 3 0.125 0.053 (atm) 4 0.131 0.074

1.25 0.110 0.031 Effect of sweep-to- 1.50 0.121 0.041 feed ratio 2.00 0.131 0.058

(a)

(atm) (atm)

2 0.062 0.042 Effect of feed pressure 3 0.084 0.084 (atm) 4 0.095 0.127

1.25 0.062 0.042 Effect of sweep-to-feed 1.50 0.076 0.060 ratio 2.00 0.093 0.095

(b)

Figure 2.1. Spiral wound module configurations. (a) Without sweep gas (reprinted with

permission from MTR, Inc.35), (b) Countercurrent flow with sweep, and (c) Crossflow

with sweep. Both (b) and (c) reprinted from Reference 36. 36

Figure 2.2. Schematic of a spiral-wound membrane reactor. (a) Countercurrent spiral- wound membrane reactor housing the WGS catalyst on the feed side, (b) Countercurrent

mode, and (c) Crossflow mode.

5 Retentate CO (ppm,dry) Conc. Retentate 0 0 20 40 60 80 100 Dry Feed Flow Rate (cc/min)

Figure 2.3. Comparison of model predictions and experimental data reported by Zou et

al.12 The solid curve is predicted by the model.

1.0E+06

1.0E+05 4.7%

1.0E+04 CO2

1.0E+03 400 ppm 487 ppm CO 1.0E+02 Countercurrent Cocurrent

1.0E+01 <10 ppm Concentration (ppm, dry) (ppm, Concentration

1.0E+00 0 20 40 60 Reactor Length (cm)

Figure 2.4. CO and CO2 concentration profiles (dry basis) along the length of the

membrane reactor.

Figure 2.5. Concentration profiles. Top: CO and Bottom: CO2 concentration (dry basis)

on the feed side for the crossflow mode.

160 Feed Side 150 Sweep Side

Countercurrent C) ° 140

130 Cocurrent

120 Temperature ( Temperature 110

100 0 5 10 15 20 Reactor Length (cm)

Figure 2.6. Feed and sweep side temperature profiles for different flow configurations.

Only the first one third of the reactor length is shown in this Figure. The profiles remain

flat for the remainder of the reactor.

150

U =20 W/m2/K

140

C) 2

° U =2.5 W/m /K

130

U =180 W/m2/K

Temperature ( Temperature 120

110 0 10 20 30 40 50 Reactor Length (cm)

Figure 2.7. Feed side temperature profiles for the countercurrent mode with three

different overall heat transfer coefficients.

150 γ = 1.25 γ = 1.25 γ = 1.5

140 γ = 2

C) °

γ = 1.5 130 γ = 2

Temperature ( Temperature 120

110 0 5 10 Reactor Length (cm)

Figure 2.8. Feed side temperature profiles for the countercurrent mode with three different sweep-to-feed ratios. Only the first one fifth of the reactor length is shown in

the Figure. The profiles remain fairly flat and predictable for the remainder of the

reactor.

Figure 2.9. Feed and sweep side temperature profiles for the crossflow configuration.

Top: feed and Bottom: sweep.

Figure 2.10. Parametric sensitivity for the crossflow configuration. Top: U at 70 times lower than the base case but at the same γ of 1.25; Bottom: γ = 2 but at the same U of 180

W/m2/K.

6,000 100

5,000

) 2

4,000 90

3,000

2,000 Membrane Area (m Area Membrane

80 (%) Recovery Hydrogen 1,000 Counter (area) Cross (area) Counter (recovery) Cross (recovery) 0 75 0.75 1 1.25 1.5 1.75 2 2.25 Feed Pressure (atm)

Figure 2.11. Effects of feed pressure on membrane area and hydrogen recovery in

reaching <10 ppm CO for countercurrent and crossflow configurations.

1,200 98

97 )

2 900 96

600 94

93 Membrane Area (m Area Membrane

300 92 (%) Recovery Hydrogen

Counter (area) Cross (area) 91 Counter (recovery) Cross (recovery) 0 90 1 2 3 4 5 Feed Pressure (atm)

Figure 2.12. Effects of feed pressure on membrane area and hydrogen recovery in reaching <10 ppm CO for countercurrent and crossflow configurations. Feed gas

composition used was 1% CO, 4% H2O, 7% CO2, 43% H2 and 45% N2.

1,200 98

) 900 96 2

600 94

93 Membrane Area (m Area Membrane

300 92 (%) Recovery Hydrogen Counter (area) Cross (area)

Counter (recovery) Cross (recovery) 91

0 90 1 1.25 1.5 1.75 2 2.25 Sweep-to-Feed Ratio (wet basis)

Figure 2.13. Effects of sweep-to-feed ratio on membrane area and hydrogen recovery in

reaching <10 ppm CO for countercurrent and crossflow configurations.

1,200 98

97 )

2 900 96

600 94

Membrane Area (m Area Membrane 300 92 Hydrogen Recovery (%) Recovery Hydrogen Counter (area) Cross (area) 91 Counter (recovery) Cross (recovery)

0 90 0 4 8 12 16 20 Steam/CO Ratio

Figure 2.14. Effects of steam/CO ratio on membrane area and hydrogen recovery in

reaching <10 ppm CO for countercurrent and crossflow configurations.

1,500 98

1,200 96

) 2 95

900 94

600 92

Membrane Area (m Area Membrane Hydrogen Recovery (%) Recovery Hydrogen 300 90

0 88 0 1 2 3 4 5 Times of membrane permeance

Figure 2.15. Effects of membrane permeance on membrane area and hydrogen recovery

in reaching <10 ppm CO for the countercurrent configuration under the same reaction

kinetics of the base case.

1,000 98

800 97

) 2

600 96

400 95

Membrane Area (m Area Membrane Hydrogen Recovery (%) Recovery Hydrogen 200 94

0 93 0 1 2 3 4 5 Times of Cu/ZnO Kinetics

Figure 2.16. Effects of reaction kinetics on membrane area and hydrogen recovery in reaching <10 ppm CO for the countercurrent configuration under the same membrane

permeance of the base case.

CHAPTER 3

SCALE-UP OF AN AMINE-BASED POLYMER MEMBRANE FOR

FUEL CELL HYDROGEN PURIFICATION

3.1 Summary

Platinum-based proton exchange membrane (PEM) fuel cells need hydrogen to be ultra-pure in terms of CO and H2S (<10 − 100 ppm, <10 − 100 ppb, respectively). In addition, CO2 capture may need to be incorporated in order to reduce the carbon footprint of the fuel cell. CO2- and H2S-selective membranes can be used in different process schemes as shown in Figure 1.2 for effective CO, H2S and CO2 removal. Previous research in our group has successfully shown that a hydrophilic blend of crosslinked polyvinylalcohol, polyamines and amino acid salt is a promising membrane material for the above separation.

To scale up a membrane, it must be produced in a high surface area per unit volume configuration. Ease of fabrication of a thin-film composite (TFC) membrane in a spiral-wound vs. a hollow-fiber configuration dictated the first step, the fabrication of a

14-inch flat-sheet membrane. For this purpose, we installed and operated the TFC assembly, a pilot-scale continuous membrane fabrication machine. We carried out

60 several runs of membrane fabrication in order to synthesize membranes with minimum defects and acceptable separation performance.

The current chapter focuses on the scale-up of membrane fabrication along with the transport characterization of scaled-up membranes. In addition, transport data from lab-scale membranes will also be discussed independently and in comparison with those of pilot-scale membranes. Preliminary results have shown that the membranes fabricated using the machine yield comparable performances to those of lab-scale membranes. The fabrication and machine operation efforts also achieved the target of producing more than

200 ft of on-spec membranes for the fuel cell project funded by the Office of Naval

Research (ONR).

3.2 Introduction

As discussed in Chapter 1, both CO2- and H2-selective membranes can be used for

PrCC and/or hydrogen purification from syngas. Based on the advantages of the former over the latter (discussed in Chapter 1), our approach to the problem involves a CO2- selective membrane at the heart of the separation process. Various mechanisms for gas separation through membranes are shown in Figure 3.1. The kinetic size of H2 molecule

53 is about 2.89 Å, which is considerably smaller than that of the CO2 molecule (3.3 Å).

For CO2-selective separation, molecular sieving or size-based separation is therefore ruled out. Some inorganic porous structures can allow surface diffusion of CO2. But such membranes are rarely studied for the above separation due to the small pore requirement

61 and consequently, low permeances. Most of the research in this area has focused on solution-diffusion and facilitated transport (FT).

It is fairly well accepted that gas transport through polymeric materials takes place by the solution-diffusion mechanism. The i/j selectivity can also be written as:

Pi Si Di i/j (3.1) Pj Sj Dj where S is the solubility and D is the diffusivity. Although the diffusivity selectivity

( D / D ) is unfavorable, the CO2 molecule has a significantly larger quadrupole CO 2 H2

54 moment and polarizability than that of the H2 molecule. These factors combined with

55 the higher CO2 condensability (critical temperatures: CO2: 304.1 K, H2: 33.2 K) mean that the solubility selectivity ( S / S ) is favorable (>1) towards its preferential CO 2 H2 transport. Polymeric materials based on ethylene oxide moieties are the most studied

56 candidates. These polar rubbery materials give a CO2/H2 selectivity of about 7 – 13.

High selectivities make it possible to avoid recompression and recycle and thereby reduce the energy consumption. Air can be used as sweep gas to provide driving force for CO2 transport and obtain high H2 recoveries as shown in Chapter 2. High selectivity is considered more important than high CO2 permeance in PrCC and for membrane-based fuel purification.8 Thus, there is a need to look beyond solution- diffusion membranes for this application.

Amines have been long used in acid gas separation. As bases, they can react reversibly with weakly acidic gases such as CO2 and H2S while not interacting with the

62 non-reactive gases like H2 and N2. The common reactions of the amines with these molecules are shown below.10,23

+ CO2 + R-NH2 + H2O R-NH3 + HCO3 (3.2)

+ CO2 + 2 R-NH2 R-NH3 + R-NH-COO (3.3)

+ H2S + R-NH2 R-NH3 + HS (3.4)

Relative to absorption, the commercial unit operation using amines, membranes provide several advantages in terms of smaller footprint and energy consumption.

Membranes employing specific chemical reactions for selective transport are said to be based on facilitated transport. In FT membranes, the CO2 molecule reacts with carrier molecules in the membrane through a selective reversible chemical reaction by which its solubility is greatly enhanced. Consequently, high selectivities for CO2/non-polar gases can be readily achieved. In the most common reactions, CO2 gets hydrated, which is then converted into a bicarbonate ion by the base (Equations 3.2 and 3.5).

2- CO2 + CO3 + H2O 2 HCO3 (3.5)

Through the above reaction, a water-soluble carbonate like potassium or sodium carbonate can also facilitate the CO2 transport. CO2 can also react with primary and secondary amines to form a carbamate ion (Equation 3.3). It is interesting to note that the reversible H2S-amine reaction (Equation 3.4) involves only a proton transfer due to which it is much faster than the CO2-amine reaction. As indicated by the above Equations

3.2 and 3.5, water aids in the CO2 uptake by the membrane which is made plausible by its presence in flue gas. In addition, water is essential as a medium or as a swelling agent to aid the diffusion of carrier-gas complexes.23

The earliest FT membranes were fabricated in “immobilized” or “contained” liquid configurations. Important disadvantages of these membranes are the fabrication and stability challenges associated with reducing the membrane thickness, sustaining a high pressure gradient and obtaining a higher productivity. In a more practical approach, the carriers can be part of a water-swollen polymer matrix. They can either be ions bound by electrostatic forces to polyelectrolytes or ion-exchange polymers, be dispersed in a hydrophilic matrix or tethered to polymeric chains of a fixed site carrier molecule.

The CO2-carrier reaction product can diffuse through the membrane (small mobile carrier molecules or ions bound to the polymeric backbone by electrostatic forces) or CO2 can

“hop” from one site to another of a fixed-site carrier molecule. On the permeate side of the membrane with a relatively low CO2 partial pressure in the gas phase, the CO2-carrier reaction product can release CO2 through the reverse reaction as shown in Figure 3.1.

Pelligrino et al. obtained a CO2/H2 selectivity of about 55 for a Nafion- monoprotonated ethylene diamine (EDAH) membrane at ambient temperature.57

Similarly, EDA-neutralized blends of poly(acrylic acid) and poly(vinyl alcohol) have been shown to exhibit high selectivities.58 Poly(vinyl benzyl trimethylammoniumfluoride) (PVBTAF), a polyelectrolyte was used to obtain selectivities greater than 200 at 23 °C.59 Polyelectrolytes and ion-exchange polymers have been combined with small molecule carriers like salts to better the separation properties. Fluoride or acetate containing salts can also facilitate the transport of CO2 like carbonate ions. Cesium fluoride has been used in blends with PVBTAF to increase the

60 CO2 permeance and obtain a respectable CO2/H2 selectivity of about 127 at 23 °C.

Salts, solely as carriers dispersed in a hydrophilic matrix or combined with fixed carrier molecules have also received attention. Ho et al. used amino acid salts and tetramethyl ammonium fluoride in a hydrophilic PVA matrix and obtained selectivities of upto 30 at ambient temperature.61,62 Ho et al. also obtained a higher selectivity of about 60 at 80 °C.

Quinn et al. used cesium fluoride in the same matrix and obtained a CO2/H2 selectivity upto 60 at 23 °C.63 Polyamines like polyallylamine (PAA), polyethylenimine (PEI) and polyvinylamine (PVAm) have been typically used as fixed carrier molecules. Being non- ionic, they offer inadequate CO2/H2 selectivities under swollen conditions unlike polyelectrolytes or ion-exchange polymers whose charged environment reduces the permeability of non-polar molecules. Polyamines have been combined with salts and studied for this separation. PEI incorporated in a matrix with PVA and lithium glycinate

64 helped increase both the CO2 permeability and CO2/H2 selectivity. PVAm-CsF, PVAm-

65 NH4F blends are examples which have been shown to provide selectivities of over 100.

3.3 Prior research on the lab-scale

Most of the above results were obtained at ambient conditions. Real syngas is at higher than 200 °C and can be at pressures ranging from a few atmospheres to about 50 bars. Also, for a PEM fuel cell, an operating temperature of higher than 100 °C is preferred since higher temperature means higher electrochemical reaction rates and better tolerance towards impurities.66,67 For a FT membrane, higher temperature usually increases both the CO2 permeability and selectivity, provided the membrane structure is stable at such a temperature. Following the work of Ho62,64, Tee at al. blended PEI with

65 formaldehyde crosslinked PVA to stabilize the membrane structure at around 100 °C.68

Zou et al. crosslinked PVA with formaldehyde/glutaraldehyde in the presence of a base

(potassium hydroxide) and blended it with polyamines and salts of amino acids.69 With

PAA as the fixed carrier and potassium salt of 2-aminoisobutyric acid (AIBA-K) as the mobile carrier, Zou and Ho obtained a CO2 permeability of about 6000 Barrers with a

23 CO2/H2 selectivity higher than 200 at 110 °C and 2 atm feed pressure. At 110 – 130 °C, an H2S permeability as high as about 3 times that of CO2 permeability was achieved

10 using a simulated syngas feed with 50 ppm H2S.

Polymeric membranes based on facilitated transport potentially combine the fabrication ease of polymeric materials with the high selectivities offered by specific chemical reactions. One disadvantage is that the permeance may not increase proportionally with a reduction in thickness. There is a need however to increase the permeances as much as possible by reducing the thickness and study the effect of thickness on separation performance. Although the membrane studied by Zou et al. was a thick (30 – 60 μm) film supported on porous polysulfone, it can potentially be made thinner by common coating techniques to obtain higher fluxes.

The chapter describes for the first time, the scale-up of the above amine-based polymeric membrane. The chemical structures of salts of simple amino acids as mobile carriers and some fixed carrier polymers are shown in Figure 3.2. Among these salts, we used AIBA-K in this study. PAA was used for lab-scale membranes while lupamin®

9095, a commercial PVAm-based product was used for scale-up.

The target thickness in scale-up was 10 – 15 μm. Knife casting was employed using the TFC assembly to fabricate a 14-inch flat sheet multilayer composite membrane

(amine containing polymer supported on porous polysulfone). Detailed description and operation of the equipment is provided in Section 3.4. After fabrication, transport properties of the membranes were evaluated and compared with appropriate lab-scale data.

3.4 Experimental

3.4.1 Materials

Two grades of Poly(vinyl alcohol), S-2217 (92+ wt%) with an average molecular weight (MW) of 150,000 g/mol and a hydrolysis degree of 87 – 89% and 217SB (94+ wt%, viscosity of 4% aqueous solution: 20.5 – 24.5 mPa-s) with the same hydrolysis degree as S-2217 were supplied by Kuraray America, Inc. (Houston, TX). The first one, an experimental grade mostly used for lab-scale experiments, is a copolymer of vinyl alcohol and 2-(acrylamido)-2-methyl propane sulfonic acid sodium salt70 while the other one, a commercial grade was used for scale-up. A third type of PVA, (99+% hydrolyzed powder, Mw = 89,000 – 98,000) was obtained from Sigma-Aldrich (St. Louis, MO) and

used for a few experiments. Poly(allylamine hydrochloride) (PAA-HCl, Mw = 120000 –

200000) was purchased from Polysciences Inc. (Warrington, PA). Lupamin® 9095 (a commercial PVAm-based product, henceforth called Lupamin®) was kindly provided by

BASF AG, (Germany). The product contained more than 60% by weight of formate salts.

2-Aminoisobutyric acid (AIBA) obtained from two vendors, Chem-Impex International

(WoodDale, IL) and Alfa-Aesar (Ward Hill, MA) was 99.46% and 99% pure respectively. 3-Aminopropyltriethoxysilane (APTEOS, 99%), glutaraldehyde (50 wt% aqueous solution), ethylene diamine (EDA) (> 99%) and potassium hydroxide (>85%) were purchased from Sigma-Aldrich. Triethylenetetramine (TETA) (> 60%) which was bought from Fisher Scientific had about 40% of cyclic and branched triethylenetetramines while linear TETA made up about 60%. Methanol (anhydrous,

>99.8%) was bought from Mallinckrodt Baker, Inc. (Phillipsburg, NJ). All the above chemicals were used without further purification. Only AIBA and PAA-HCl were neutralized with KOH before further use in the membrane preparation. TriSep microporous polysulfone supports (U-100, 140 µm thick including a non-woven fabric support) were purchased from TriSep Corporation (Goleta, CA) and used in the scale-up experiments due to their commercial availability. The NL nanoporous polysulfone support (thickness of 160 µm including a non-woven fabric support) was provided by NL

Chemical Technology, Inc. (Mount Prospect, IL). Both these supports have similar surface morphologies which are further discussed in Chapter 5.

Two types of specialty feed gas mixtures with certified compositions were purchased from Praxair, Inc. (Danbury, CT) for the gas permeation tests: one consisting of 20% CO2, 40% H2, 40% N2, and 50 ppm H2S and the other consisting of 25% CO2 and

75% N2 (all on dry basis). Prepurified argon used as sweep gas and as carrier and reference gas for gas chromatography was also purchased from Praxair, Inc. Prepurified helium and prepurified oxygen used for the operation of the sulfur chemiluminescent detector (SCD) were also obtained from Praxair, Inc.

3.4.1 Membrane preparation

3.4.2.1 PVA crosslinking

The membrane preparation procedure was similar to that reported in previous publications.23,69,10 The first step involves the preparation of partially crosslinked PVA solution. PVA (217SB) is dissolved in water at a desired concentration. After stirring overnight at room temperature, temperature is increased to 80 °C and it is vigorously mixed for two more hours. For PVA S-2217, the same procedure was used. For Sigma

PVA, the heating step is started after a few minutes of room temperature stirring. KOH solution (about 30 – 40% in water) is then added dropwise to the PVA solution under gentle stirring after which the solution is vigorously stirred for 20 minutes. At this point, the reaction is started by adding glutaraldehyde solution dropwise under gentle stirring.

This reaction is carried out for about 150 – 180 minutes after which it is stopped by transferring the reaction flask to a cold stir plate with continued gentle mixing. On the lab-scale, the above reaction was carried out in a 125 ml conical flask with a magnetic stirrer. About 25 – 30 ml of reaction mixture was used. For PVA S-2217 and Sigma

PVA, the concentration of crosslinked PVA was kept at 12 – 13% while that of KOH was kept at 3 – 4%. These numbers were kept at 8 – 9% and 3 – 4% respectively, for PVA

217SB due to its greater propensity to salt out. Glutaraldehyde amount was calculated for a given mol% crosslinking and the initial PVA amount.

On the pilot scale, the procedure remained the same except for a few differences.

The crosslinking reaction was carried out in a 500 ml glass conical flask which was modified to introduce a second inlet. The top inlet was used to introduce an overhead

69 stirrer which was controlled by an external rpm controller. The second inlet was used to introduce KOH and glutaraldehyde into the solution under stirring. The reaction mixture volume in this case was about 200 – 250 ml, about 10 times of that prepared on the lab- scale.

3.4.2.2 Carrier solution and final casting solution preparation

Lupamin® was used as received. AIBA was neutralized in a solution of KOH at room temperature and stirred for at least one hour to prepare AIBA-K solution. Similarly,

PAA-HCl was reacted at room temperature for at least 24 hours with KOH in methanol.

The precipitated KCl was separated from the homogeneous PAA solution in methanol by centrifugation (8000 rpm, 10 minutes). The solvent methanol was replaced with water under nitrogen before its final use. Before preparing the final casting solution, lupamin® or PAA solution in water was mixed with AIBA-K solution to yield an appropriate solids concentration. The amine solution was then added dropwise to the crosslinked PVA solution. At this stage, it is vital to have the solids concentration low enough to avoid instantaneous gelling of the casting solution. Bulk mixing is important initially when the solution is relatively less viscous while high-shear mixing is important later at higher viscosities. The solution height was kept close to the height of the stir-bar as far as possible.

The mixing was continued for about 30 minutes to 1 hr depending upon the starting concentration of the casting solution. The solution thickness was then evaluated visually to determine a honey-like appearance with high extensional viscosity. Basically, the solution concentration was kept as high as possible in order to obtain a highly viscous

70 and homogeneous casting solution. The casting solution concentration varied depending upon the membrane composition, ratio of PVA/fixed carrier polymer, type of fixed carrier polymer and the presence of gelling inhibitors like triethylenetetramine (TETA), ethylene diamine (EDA) etc. The solution amount was about 5 – 6 ml in a 50 ml beaker.

The solution was centrifuged to remove any air bubbles for about 2 minutes at 8000 rpm just before casting. The cast was then made using a GARDCO stainless-steel film applicator on a support flattened on a glass plate. The gap setting can be adjusted to control the thickness of the wet film and the final membrane thickness. After the cast, the membrane was dried overnight in the hood and then for six hours at 120 °C. This was the most common curing condition for the lab-scale membranes reported in this chapter. Any deviation from the procedure has been mentioned wherever required.

On the pilot-scale, the total solution amount was about 200 – 300 ml. The mixing was done in a closed container with overhead stirrer. The amine solution was added in about five or six batches. During addition, the lid was opened and stirring was stopped momentarily. After about 45 minutes to 1 hr, the solution viscosity was inferred by measuring the time required for a fixed amount of solution (~23 ml) to drain through a standard glass conical flask. When this time reached the desired point (>5 minutes), the mixing was stopped and the solution was centrifuged. Also, an appropriate amount of

EDA or TETA was mixed/reacted with the crosslinked PVA for about an hour prior to adding the carrier solution on the pilot-scale. This was necessary to delay the gelling as explained in Section 3.4.3. On the lab-scale, this step was not required since only a small piece of membrane had to be cast. However, some membranes with EDA or TETA in the

71 casting solution were also cast on the lab-scale. The pilot membrane fabrication using the

TFC assembly has been discussed in Section 3.4.4.

3.4.2.3 Other considerations

60 mol% degree of crosslinking was used for the lab-scale experiments while 15 mol% was used for the pilot-scale preparation. The lower degree of crosslinking on the pilot-scale was mainly driven by the need to prolong the life of the casting solution (see

Section 3.4.3). PVA S-2217 was used for all the lab-scale experiments and for a few pilot-scale runs. PVA 217SB and Sigma PVA were used only for the pilot-scale experiments due to their commercial availability. In most of the experiments, PVA

217SB was employed. Since PVA does not contribute to transport directly, the differences among the different PVA grades are not expected to cause significant variation in the membrane performance as long as the casting solution is viscous and homogeneous and the membrane has enough PVA to support its structure. As mentioned before, they do necessitate small changes in the concentrations etc. to obtain a good casting solution. Among PVA 217SB and Sigma PVA, the former, presumably due to its higher molecular weight and lower degree of hydrolysis and consequently, a lower surface tension (of the aqueous solution) gave a better coating with fewer macroscopic defects. Since non-scientific reasons such as availability or the lack of it dictated the choice of PVA and also the differences are not expected to significantly affect the membrane performance, the type of PVA and its influence on membrane properties are not further discussed.

3.4.3 Gelling

The above casting solution contains crosslinked polyvinyl alcohol blended with polyamines. The crosslinking reaction of PVA by glutaraldehyde is shown in Figure 3.3a.

The reaction cannot go to completion since it is equilibrium limited and water, a product of the reaction is the solvent. More importantly, the reaction is accompanied by a side reaction of glutaraldehyde self-polymerization to polyglutaraldehyde in the presence of a strong base (Figure 3.3b).71,72 The conjugated aldehydic groups in polyglutaraldehyde can react with amines over a wide pH range.71 This reaction seems to proceed with polyamines even at room temperature to presumably form a network and cause the observed gelling of the casting solution.

To reduce the rate of gelling, we explored small amines as membrane components. The small amine molecules react with the aldehydic groups in solution but their products do not have a large enough molecular weight to gel or precipitate as insoluble species. The interference reduced the extent of reaction with the polyamines. As a result, the gelling was somewhat inhibited due to which the time before gel formation or „gel time‟ (henceforth referred to as the „life‟ of the casting solution) was increased.

We used small reactive primary amines with more than one amino group, ethylene diamine (EDA) and triethylenetetramine (TETA) for this purpose.

TETA: H2N-CH2-CH2 –NH-CH2 -CH2 –NH-CH2 -CH2 -NH2

EDA: H2N-CH2-CH2 –NH2

To prove that this concept will work, we carried out a simple set of three experiments. In the first one, we mixed 4.4 g of crosslinked PVA with 1.3 g of

Lupamin®. The solution gelled within seconds of mixing. In the next two, we added about 2.3 g of TETA and 2.3 g of APTEOS respectively, to the crosslinked PVA solution and mixed for 10 minutes or so before adding the Lupamin®. The final solution was then mixed for 10 minutes or so and then allowed to stand. The one with TETA did not gel in

24 hours while the one with APTEOS gelled in about 70 minutes. The gelling was evaluated visually and from the viewpoint of whether a cast (or membrane) could be obtained. Although the ratios used in the above set of experiments were much different from the standard membrane compositions, the results did indicate a pattern in delaying the gelling phenomenon. Also, the comparison with APTEOS which has only one amino group per molecule and a higher molecular weight than TETA (molecular weights 221.4 and 146.2 for APTEOS and TETA, respectively) showed that the increase of „gel time‟ was not merely a dilution effect.

3.4.4 Thin-film casting (TFC) assembly

The TFC assembly is a part of the coating machine which has three sections; the coating assembly, rinse tank and the TFC assembly (Figure 3.4). The machine as a whole can be used to fabricate state-of-the-art desalination membranes. The TFC assembly can also be used as a stand-alone equipment to fabricate multilayer composite films/membranes by knife-casting. The support (U-100) roll was initially extended all the way from the unwind end to the rewind end according to the specified threading path.

The load cell rollers at the unwind and rewind ends have to be calibrated regularly using a known 10-pound weight. The motion of the web is controlled using a separate control panel for the coating machine. On the front side of the panel, there are five basic items; 1)

74 the human machine interface (HMI) which is a touch-screen panel that accepts user inputs for machine control, 2) drive „start‟ button, 3) drive „stop‟ button, 4) „jog‟ button and the 5) „emergency stop‟ button. The HMI has two main pages under the „drive configuration‟ heading. On selecting the „thin film cast‟ configuration, the screen shows the two main user input parameters; unwind tension and the web-speed. The „clear drive faults‟ can be used to clear the faults and restart the drive if the rewind end has faulted.

The „jog‟ functionality on the HMI should be used along with the main „jog‟ button on the panel to move the drives in any direction independent of each other. This is especially useful during web threading and to clear any high tension situations during the operation.

The web speed can be adjusted upto 5 ft/min. The tension was set at 18 pounds for most runs in order to lay the support perfectly flat at the knife. In addition, in order to ensure that the support did not come up during the run, a smooth stainless steel (about 21 inches in width) rod was kept on the moving web just behind the knife. Polypropylene dams were used to prevent the casting solution in the trough from escaping through the sides. This set-up near the casting region of the TFC assembly is specifically shown in

Figure 3.5. The speed was set at 0.5 or 1 ft/min with 0.5 ft/min as the set-point for most runs.

The gap between the granite slab and the knife edge was fixed at a particular value before a run using filler gauge. For a given gap and the total support thickness, the gap setting (gap between the knife edge and substrate to be coated) can be calculated and correlated with final membrane thickness. At 0.5 ft/min, the residence time for the web inside the oven was about 16 minutes. The oven of the TFC assembly was supplied with

75 hot air from a corresponding skid on the roof. The temperature of the hot air and flow rate could be controlled by a separate control panel. The incoming and outgoing flows were adjusted to obtain a small negative pressure inside the oven. The incoming flow was set at 50 – 60% for most runs while the outgoing flow was set at the maximum. The temperature of the hot air at the outlet of the skid was adjusted using the control panel and calibrated to obtain about 125 – 130 °C at the oven inlet. With 16 minutes of residence time, the membrane was dry at the oven exit and the curing was assumed to be complete. The thicknesses of the multilayer lab- and pilot-scale membranes were measured after drying using the Mitutoyo Electronic Indicator (Model 543-252B,

Accuracy ±0.5 μm, Mitutoyo America Corporation, Aurora, IL). The support thickness was separately measured which was then used to determine the thickness of the selective layer thickness. Both the support and the total membrane thickness were measured at a minimum of 20 points near the beginning of the membrane. The standard error in the measurement was less than 1%.

3.4.5 Gas permeation set-up and transport measurements

The gas permeation set up shown in Figure 3.6 was used to test the membranes for their separation performance. This set-up consists of mass flow controllers, water pumps and humidifiers to simulate the real gas compositions. The membrane is sandwiched between the upper and lower parts of a permeation cell. The feed and sweep gases enter the cell in the top and bottom section respectively, in a contercurrent configuration. The retentate and permeate streams then enter the Gas Chromatograph

(GC) for composition analysis after water removal. Thermal conductivity detector (TCD)

76 was used for all the gases except H2S. For H2S analysis, SCD from Antek instruments

L.P. (Houston, TX) was used. The compositions of the gases along with mass balances and flux equations can then be used to calculate the membrane performance. Unless mentioned specifically otherwise, all the results reported in this chapter were obtained using the circular cell of area 45.6 sq.cm. We also installed a small rectangular cell (area:

2.71 sq.cm) shown in Figure 3.6 for accurate high permeance measurements. This is further discussed in Section 3.5. The differences between the two cells and the assumptions involved in calculating the membrane performance have been discussed in

Section 3.5.2.

3.4.5.1 Test conditions

As mentioned before, two types of gases were used. The first one had 20% CO2 along with H2 and N2 and the second one had 25% CO2 and 75% N2. For the first gas, the feed and sweep flow rates were 60 cc/min and 30 cc/min on dry basis with water flow rates for both sides kept at 0.03 g/min. The temperature and base feed gas pressure for the tests were 106 °C and 15 psig respectively. For the 25% CO2 containing gas, the feed flow and base feed pressure were reduced to 48 cc/min and around 11 psig in order to have the same CO2 and water partial pressures above the membrane as the gas with 20%

CO2. This gave a legitimate comparison of membrane performances measured with different gases since CO2 and water partial pressures are critical parameters affecting membrane performance.23

3.5 Results and discussion

3.5.1 Membrane quality and defects

Figure 3.7 shows the top surface image of a scaled-up flat-sheet membrane taken from a standard digital camera. The final membrane had a few elongated defects or thin spots. High tension combined with the high extensional viscosity probably gave rise to these defects. At lower than optimal viscosities, white circular spots appeared as defects.

In any case, high viscosity was preferred due to fewer defects which could be hand- patched and a lower possibility of infiltration of the casting solution into the support pores.

3.5.2 Transport characterization

Prior to scale-up, we synthesized a series of membranes to establish a basis for future comparison of results. These lab-scale membranes were characterized for their separation performance and the transport measurements have been shown in Table 3.1.

All these membranes had about the same composition: 46.2 % crosslinked PVA, 17.5%

KOH, 26.5% AIBA-K and 9.8% PAA. The membrane #L-1 had a thickness of about 28

μm and gave a CO2 permeability of >6200 Barrers which is comparable to the past results achieved by our group at 100 – 110 °C and 2 atm feed pressure for similar membrane compositions.23 Other membranes in Table 3.1 have lower thicknesses. With a lower thickness, the CO2 permeance increases but the increase is not proportional to the magnitude of thickness reduction.

It is now worth mentioning the effect of stage-cut in these measurements. Stage- cut is defined as the ratio of CO2 flow rate permeating through the membrane to that in 78 the feed. Higher the stage-cut, higher is the difference between inlet and outlet CO2 concentrations. All the results shown in Table 3.1 except the last one have been obtained using a circular cell of area 45.6 cm2 which was also used in all prior work at low pressure. Generally, for such geometry, „mixed flow‟ is assumed on both the feed and permeate sides of the membrane. In that case, the outlet concentrations are used to calculate the driving force across the membrane. If the stage cut is high, the difference between the inlet and outlet concentrations will be high due to which the „mixed flow‟ assumption might not hold well for estimating the actual driving force.

In this case, the flow can be modeled using a 1-D model similar to that studied previously by Huang et al. or the one that will be discussed in Chapter 4 where the concentrations on both the feed and permeate sides vary continuously. In order to minimize axial mixing, a rectangular geometry is preferred. For this purpose, we used a newly fabricated small rectangular cell shown in Figure 3.6 for some of the transport measurements reported in this chapter and all the results reported in Chapter 6. For this cell, we confirmed that the model can be accurately represented by a log-mean partial pressure driving force for the transport measurements reported in this chapter. This was convenient for routine calculations.

For the circular cell, however, modeling the flow is significantly more difficult.

So, in order to analyze the results more thoroughly, we calculated the CO2 permeance using both the mixed-flow assumption as well as a log-mean partial pressure driving force. It should be remembered that the actual result for the circular cell is expected to lie somewhere between the two values. For instance, as seen in Table 3.1, for a 3 μm

79 membrane (#L-4), the CO2 permeance is about 280 GPU when measured using the rectangular cell. This value is obviously considerably higher than that expected using the trend of log-mean permeances for the other membranes (#L-1 to #L-3) and is significantly lower than that expected from the mixed-gas permeances. It should be noted that the selectivity reported in Table 3.1 has been calculated as a ratio of permeances obtained through log-mean driving force (unless mentioned otherwise). A CO2/N2 selectivity of over 2000 is consistent with a CO2/H2 selectivity of > 200 according to prior lab-scale data for thick membranes.69,73

In all the succeeding discussions, we will focus on pilot-scale membranes. These membranes have a somewhat different composition from the above lab-scale membranes.

So, a one-on-one comparison with previous data is not feasible. Nevertheless, the differences in the compositions are not expected to cause major variations in the transport performance. In the initial part of the scale-up efforts, we used TETA to prolong the life of the casting solution. Runs #3, #4, #30 and #32 in Table 3.2 are examples of the same.

The membrane performances show a similar trend with respect to thickness as seen in

Table 3.1. Membrane 1 (Run #3) gave a CO2 permeability of over 6300 Barrers. This permeability combined with a CO2/H2 selectivity of over 200 for thick membranes is consistent with what was achieved previously.69

We then looked at EDA instead of TETA in the membrane. One advantage of

EDA is that due to its volatility (Boiling point of 118 °C vs. 280 °C for TETA); it has a much greater probability of being removed from the membrane during the drying process. Also, EDA is expected to be more effective on a weight basis as a gelling

80 inhibitor since it has two amino groups for a molecular weight of 60.1 whereas TETA has four for 146.2. We did observe an increase in the average life of the solution with EDA. It increased to about 40 minutes from about 30 minutes obtained with TETA.

In Table 3.3, the lab-scale membranes differ in the amount of carriers in their composition, especially in the proportion of KOH in the membrane. This can explain the difference in the permeances obtained for the two membranes (#L-6 vs. #L-5). In this case, the lab-scale membranes are prepared with EDA and dried in the convective oven for 16 minutes from both sides instead of the standard procedure used for previous lab- scale membranes. The lab-scale membrane (#L-6) shows good agreement with Run #40 membrane indicating agreement between lab-scale and pilot-scale procedures with EDA.

Although Table 3.3 compositions were calculated assuming EDA will be retained in the membrane, they may be somewhat different depending upon how much EDA can be removed during drying. More experiments and other type of analysis using FT-IR or thermogravimetry may be required to find this out.

We also measured the H2S/CO2 permeance/permeability ratios for different scaled-up membranes. A ratio of about 3 – 4 was expected from prior data.10 The ratio varies between 2 and 4 in Table 3.3. In Table 3.2, the ratio of 41 for Run #30 just indicates the effect of stage-cut error on this measurement. Because of the higher permeability of H2S vs. CO2, the magnitude of this error is greater for H2S. Comparing membrane #L-6 with Run #30, the ratio seems to increase with the permeance which is again consistent with the explanation due to stage-cut error. On the other hand, the ratio calculated by log-mean permeances varies between 2 and 3 in both the tables. This could

81 be an underprediction due to the afore-mentioned limitation of log-mean calculation for the circular cell. So, we characterized Run #54 membrane in the rectangular cell for both

CO2 and H2S data. It can be inferred from Table 3.3 that a CO2 permeability of 3200

Barrers (100 Barrers translates to 100 GPU for a 1 μm membrane) was measured in the rectangular cell for that membrane. Whereas for Run #40, log-mean calculation gives a

CO2 permeability of about 2500 Barrers. This again suggests how the rectangular cell can give a higher number compared to log-mean permeance calculated using the circular cell.

Also, a ratio of >4 is measured for H2S/CO2 ratio which is again higher than that obtained using circular cell and log-mean permeances for Run #40.

Run #47 membrane was characterized to determine the effect of temperature and pressure on pilot-scale membrane performance. At the base pressure, a CO2 permeability of about 3070 Barrers was measured which agreed reasonably well with Run #54. The effect of pressure and temperature is shown in Figure 3.8. We can see the competing effects of carrier saturation and relative humidity on the separation performance as the pressure is increased. Carrier saturation reduces the measured CO2 permeance while a higher relative humidity can increase the performance.69,23,74 As the pressure increases from 1 atm to 1.5 atm, initially the performance is lower since the relative humidity is lower and it controls the trend in the performance. As the pressure increases, the carrier saturation also starts playing a greater role due to which the performance stabilizes at around 1.5 – 2 atm. After this, when the pressure is increased further at the same relative humidity (feed water flow rate was changed to keep the water partial pressure same for the points at about 2.1 and 2.7 atm), the performance drops due to carrier saturation.

When the temperature is increased from 106 °C to 110 °C, the performance drops which is consistent with our previous results. This occurs because the lower water retention in the membrane at higher temperatures can more than negate the higher reaction rates.

Figure 3.9 shows the effect of membrane thickness on CO2 permeance measured using the rectangular cell and reported in this chapter. Although these membranes have somewhat different compositions, the trend is nevertheless informative. The amount of mobile carriers is between 40 to 43% in these membranes. A CO2 permeance of about

280 GPU was obtained for a 3.5 μm membrane.

As part of our scale-up efforts, we carried out more than fifty runs of membrane fabrication using the TFC assembly. Some of the initial runs gave only around four to five feet of good membrane while the later runs gave an average of about 20 ft of good membrane. Table 3.4 shows some of the details of the runs whose membrane products were sent for fabrication into a spiral-wound module. Such a module will then be used for hydrogen purification as part of the ONR project.

3.6 Conclusions

1) The thin-film casting assembly capable of fabricating 14 to 21-inch flat-sheet

membranes was successfully installed and operated to scale up the amine-based

polymer membrane for high temperature fuel cell application.

2) In order to keep the web flat on the granite slab during coating, a stainless steel rod

was placed and allowed to rotate on the moving web behind the knife. This

modification helped us to fabricate reproducibly a flat-sheet membrane of thickness

10 – 15 μm with a width of at least 12 inches.

3) Over the course of more than 50 runs, the fabrication process was slowly improved to

reduce defects, prolong the life of the casting solution and improve the membrane

performance till more than 200 ft of on-spec membrane was shipped for spiral-wound

membrane fabrication. Thus, the facilitated transport membrane with lupamin® (fixed

carrier PVAm) and AIBA-K as the mobile carrier was successfully scaled-up.

4) Some of the above membranes were characterized for their transport performance. A

CO2 permeability of over 3000 Barrers was measured for a 15 μm thick membrane.

The performance showed good agreement with previous data with thick membranes

and current lab-scale results. CO2/H2 selectivity was around 200 or more, which as

seen in Chapter 2, can provide a H2 recovery of close to 95% or higher for fuel cell

hydrogen purification.

5) The effect of thickness on CO2 permeance was studied. The CO2 permeance increased

with thickness reduction but the increase was not proportional which was consistent

with facilitated transport. A maximum permeance of about 280 GPU was measured

for a 3.5 μm membrane under the given test conditions.

Acknowledgments

The authors would like to thank the Office of Naval Research (N00014-11-C-0062),

DJW Technology, LLC, and The Ohio State University for the financial support of this work.

minutes. $The selectivity is the ratio of log-mean permeances.

$ Membrane # lm (μm) PCO2, lm PCO2, mx αCO2/N2

(GPU) (GPU)

L-1 28.1 133 223 2222

L-2 11.0 144 260 962

L-3 5.5 163 335 441

L-4 3.5 280 286 335

(Rectangular Cell)

Table 3.2. Transport characterization of pilot-scale membranes with TETA using a CO2-

H2-N2 gas mixture. All the runs had about 8 – 9 % TETA in their final membranes. Run

#3: 33% crosslinked-PVA, 13% KOH, 22% AIBA-K, 22% Lupamin® and 3% APTEOS.

Run #4: 33% crosslinked-PVA, 13% KOH, 22% AIBA-K, 21% Lupamin® and 3%

APTEOS. Run # 30: 29% crosslinked-PVA, 14% KOH, 26% AIBA-K, 23% Lupamin®.

Run #32: 34% crosslinked-PVA, 13% KOH, 27% AIBA-K, 17% Lupamin®.

* $ Test gas contained no H2S. Measured using CO2-N2 gas mixture

and in the rectangular cell.

Run # lm PCO2,lm PCO2,mx αCO2/N2 αCO2/H2 αH2S/CO2,lm αH2S/CO2,mx

(μm) (GPU) (GPU)

3* 29.3 141 218 1385 241

4* 20.6 157 270 1245 182

30 11.5 174 356 1953 119 2.8 41

32$ 12.0 241 245 685 -

Table 3.3. Transport characterization of pilot-scale membranes with EDA using a CO2-

H2-N2 gas mixture. All the runs had about 8 – 9 % EDA in their final membranes. Run

#40: 28% crosslinked-PVA, 18% KOH, 22% AIBA-K, 21% Lupamin® and 3%

APTEOS. Run #54: 31% crosslinked-PVA, 17% KOH, 23% AIBA-K, 21% Lupamin® and 3% APTEOS. Membrane # L-5: 33% crosslinked-PVA, 12% KOH, 23.5% AIBA-K,

23% Lupamin®. Membrane # L-6: 26% crosslinked-PVA, 18% KOH, 24.5% AIBA-K,

® * 23.5% Lupamin . Measured in the rectangular cell and N2 peak too small to calculate the

selectivity.

Run or lm PCO2,lm PCO2,mx αCO2/H2 αH2S/CO2,lm αH2S/CO2,mx

Membrane# (μm) (GPU) (GPU)

Pilot-scale

40 17.2 146 310 318 2.1 2.7

54* 14.6 219 218 182 4.3 4.4

Lab-scale

L-5 12.3 141 291 187 2.3 3.3

L-6 14.5 156 356 334 2.3 3.8

Table 3.4. Thicknesses and lengths of membranes fabricated using the TFC assembly and sent for spiral-wound module fabrication. The membrane composition was kept the same

in all these runs. The membranes had about 30 – 31% crosslinked PVA, 16.6 – 17%

KOH, 22.5 – 23% AIBA-K, 20 – 21% Lupamin®, 8 – 9% EDA and 0 – 2.5% APTEOS.

APTEOS was added in the casting solution to reduce frothing if observed.

Run # lm (μm) Length (ft)

43 12.5 14.0

44 14.5 19.0

45 13.6 25.6

46 13.7 10.7

47 15.7 20.0

48 13.3 19.9

50 12.0 23.0

52 12.9 18.0

53 11.8 20.6

54 14.6 15.0

56 15.8 20.0

Figure 3.1. Mechanisms for separation through membranes

Figure 3.2. Chemical structures of salts of some amino acids as mobile carriers

and polyamines as fixed carriers.

O OH O OH OH OH KOH CH2 CH HC H O CH + 2 + CH2 2 O CH4 OH O

O CH CH2 CH O

CH 2 CH2

(a)

O O O KOH CH CH O O CH 2 CH2 CH C CH2 CH2 nH O n + 2 CH2 CH2

(b)

Figure 3.3. (a) Crosslinking of PVA with glutaraldehyde, (b) Side reaction of

polyglutaraldehyde formation under the same conditions.

Figure 3.4. Pilot-scale membrane fabrication machines. Top: Schematic of the

coating machine. Bottom left: Actual TFC assembly in operation and

Bottom right: Schematic of TFC assembly.

(a) Top view

(b) Front view

Figure 3.5. Casting trough region of the TFC assembly. (a) Top view and

(b) Front view.

N Purge 2 Oven Water Reservoir Humidifier Water Back Water Knockout Pressure Pump Regulator

Permeation Feed Gas Cell

GC Mass Flow-meter

Water Reservoir Humidifier Vacuum Water Pump Pump

Water Knockout Sweep Gas or Cold Trap

Mass N2 Purge Flow-meter

Figure 3.6. Gas-permeation set-up and the small rectangular cell

Figure 3.7. 14-inch amine-based flat sheet polymer membrane fabricated using the TFC

assembly.

3500

3000

2500

2000

1500 110 C

1000 Feed water flow reduced

Permeability Permeability (Barrers) to 0.02 g/min 2

500 CO

0 0 0.5 1 1.5 2 2.5 3 Feed Pressure (atm)

Figure 3.8. Effect of temperature and pressure on CO2 permeability for Run #47. For this, a CO2-N2 mixture gas was used which had an unusual composition (determined based on

GC analysis) of 30.5% CO2 and rest N2. To ensure comparison with results obtained

using other gases, the dry gas flow rate was reduced to 40 cc/min and the base feed pressure was reduced to about 1.5 atm. The base temperature was 106 °C with water flow

rates kept at 0.03 g/min on both feed and sweep sides.

300

250

200

150

Permeance Permeance (GPU) 100 2

CO 50

0 0.0 5.0 10.0 15.0 20.0 Membrane Thickness (μm)

Figure 3.9. Effect of membrane thickness on CO2 permeance. All the measurements

carried out in the rectangular cell and reported in Tables 3.1 to 3.3.

CHAPTER 4

MEMBRANE PROCESSES FOR CARBON CAPTURE FROM COAL-FIRED

POWER PLANT FLUE GAS: A MODELING AND COST STUDY

4.1 Summary

Favorable economics of electricity generation will be crucial to the successful implementation of post-combustion carbon capture. Hence the US DOE has set a goal of

<35% for the increase on the cost of electricity (COE) due to CO2 capture. For meeting this goal, there is thus a growing need to perform a cost analysis of emerging separation methods. This chapter goes through a detailed modeling and cost-sensitivity study of a promising membrane-based process for carbon capture: the air-sweep process. We have studied the impact of membrane performance, selectivity and permeance, on the COE increase and the capture cost. The effects of operating parameters as well as the membrane price on the overall cost were determined. Cost calculations show a COE increase of about 33% along with a capture cost of <$24/ton CO2 for the air-sweep process to achieve 90% CO2 recovery and 95% purity of the CO2 product. This process operates at slightly above atmospheric feed pressure (about 1.1 atm) with feed compression for cost optimization and requires a low membrane module price of $2.5/ft2

2 ($27/m ), a CO2/N2 selectivity of about 150 combined with a high CO2 permeance of

3000 GPU. Although the required membrane properties have not yet been achieved, this research emphasizes quantitatively the need to improve the present membranes to realize a purely membrane-based process for the above application.

4.2 Introduction

According to the International Energy Agency report on world energy statistics, coal accounted for 25% of the world electricity and 42% of the world CO2 emissions at about 29 billion metric tons in 2007.75 In the absence of any international agreement on greenhouse gas (GHG) reduction, the coal use is projected to increase by more than 55% in 2035 with about 95% of the increase contributed by China and India.76 The coal-fired electric power sector contributes about 33% of CO2 emitted by all the fossil fuel sources

(coal, petroleum and natural gas) in the US.77 Thus, it is amply obvious that cost- effective reduction of CO2 emissions from the coal power plants will be the most important GHG reduction activity in the coming decades.

Post-combustion capture is one of the three general approaches to capture CO2 emitted by large point sources such as coal-based power plants. The other two are pre- combustion capture and oxy-combustion. 4,6 These two require extensive redesign of the power plant itself, and hence could only be an alternative for the new power plants. But, most of the new plants are conventional pulverized coal-based using air for combustion.78

For these plants and the existing fleet of more than five hundred 500-MW conventional coal-fired power plants78, post-combustion capture seems to be the only effective way to reduce the CO2 emissions. Since it can be retrofitted to the existing power plants, it

99 would be a means to produce carbon-constrained energy without extensive capital spending needed for the other two methods.

Most of the detailed studies on process modeling and economics of post-

5,79,80,81,82 combustion CO2 capture have focused on amine scrubbing. This is mainly because this process has already been demonstrated on large scale for CO2 separation from natural gas and synthesis gas, and hence is a mature technology.82 The drawbacks of this process include expensive steam regeneration, polishing for SO2 removal, amine losses, and corrosive liquid handling. The associated costs become more evident when applied to post-combustion CO2 capture. An economic analysis performed by the

National Energy Technology Laboratory on a state-of-the-art (SOTA) amine process shows about 85% increase on the cost of electricity (COE)5,81 or a capture cost of close to

$50/ton CO2. Optimistic studies considering process and solvent improvements for the amine process have projected an energy consumption of about 25% of the typical power plant output.82 Hence the cost and energy penalties associated with this relatively mature technology show the challenges of integrating CO2 removal cost-effectively into a conventional power plant. Moreover, the Department of Energy (DOE) has set a stringent target of 35% increase on the COE where the cost includes not only the cost of

6,81 the separation step for 90% CO2 recovery with at least 95% purity , but also that of compressing the purified CO2 stream to the pipeline pressure of 2200 psia along with the associated transport, storage and monitoring (TS&M) costs.81

The membrane community has lately paid considerable attention to finding suitable alternatives to the amine process.83,84,85,86,87,88,89,90,91,92 Single-stage processes to

100

84,85,88,90,92 meet lower CO2 recovery and purity requirements have been studied. Few studies have also looked at multi-stage processes combining process modeling with economics.83,86,87,89,91 In our view, none of the studies so far have explored systematically the membrane processes in relation to the cost and performance targets for carbon capture. This study aims at an elaborate assessment of the impact of important process parameters and membrane performance on the final costs using a fairly detailed economic analysis. In addition, it provides insights into process optimization by combining modeling with cost-sensitivity analysis. Also it indicates the need to improve existing membranes or develop advanced membranes with better performance.

4.3 Membrane processes for carbon capture

4.3.1 Challenges

In addition to the membrane properties, the separation achieved by a membrane process depends on the available driving force for mass transfer through the membrane.

Considering two components i and j, i.e., CO2 and N2, respectively in flue gas (where CO2 is the more permeating component), the flux Ji of component i and membrane selectivity

αi/j of component i over component j are defined as follows:

J i = Pi ( p f × X i - ps ×Yi ) (4.1)

Pi α (4.2) i/j P j

The purity of the CO2 product, which is ultimately determined by the relative fluxes of CO2 and N2, depends on not only the selectivity but also the pressure ratio 101

25,83 (pf/ps). For a given selectivity, higher purity can be achieved for a larger pressure ratio. On the other hand, the higher the selectivity, the smaller is the pressure ratio required to achieve a desired purity. This fact means that higher selectivity can reduce the energy consumption as explored by previous studies. 84,85 This is important since in a post-combustion scenario, the flue gas pressure after desulfurization is about 1 bar with a

5,78,79 CO2 concentration of 10 – 15% on wet basis. Energy associated with generating the pressure ratio by compression or vacuum means that the ratio is limited to about 5 – 10, as was recently emphasized by Merkel et al.83 But, in a regime of a limited pressure ratio such as this, both a higher purity and a smaller pressure ratio can increase the membrane area significantly. Thus, an optimum selectivity is expected.

CO2 recovery, which is affected by the CO2 flux through the membrane, directly influences the membrane area requirement. Low CO2 partial pressure, high recovery and purity targets translate to a low average driving force in a membrane module. To counter this, a high CO2 permeance is preferred (from Equation 1) to reduce the membrane area especially in a pressure ratio-limited separation. Furthermore, since recovery and purity are closely related, the purity attained reduces significantly as the recovery increases, especially at higher recoveries of more than 80%.84 Thus, high purity and recovery targets pose significant challenges to a membrane process, demanding both a high performance membrane and an increased driving force.

4.3.2 Strategies to increase driving force

4.3.2.1 Feed compression

102

Increasing the driving force by feed compression would also mean compressing a large amount of nitrogen present in flue gas. This results in a huge energy cost.

4.3.2.2 Vacuum on the permeate side

Since the permeate is richer in CO2, the molar flow rate of the permeate stream will be less than that of the feed stream so that the ideal energy consumption of a vacuum pump on the permeate side will be less than that of a feed compressor for the same pressure ratio.84,85 A permeate pressure of <0.2 bar may not be feasible with state-of-the- art industrial scale vacuum pumps.83 However, some studies have mentioned a lower threshold of 0.03 bar.84,85,86

4.3.2.3 Sweep gas on the permeate side

The third method to increase the driving force is to use a sweep gas on the permeate side.24,25,83 The obvious, technically feasible option is to use low pressure steam as sweep gas. But, it requires a huge amount of energy to produce steam unless low- pressure waste (free) steam is available in some power plants. Researchers at Membrane

Technology and Research, Inc.83,93 studied a process using combustion air as sweep to increase CO2 concentration in the flue gas. Another possibility is to use a small amount of retentate (the treated flue gas in this context) as the sweep gas.94

Besides the three strategies discussed in Sub-sections 4.3.2.1 to 4.3.2.3, recycling a part of the permeate stream to boost the CO2 concentration on the feed side can also be pursued as an alternative.94 But this will increase the energy load on the vacuum pump due to the increased flow rate to the pump, and is not likely to be cost-effective.

103

4.3.3 Multi-stage air-sweep process

25,83,84,85 Due to the partial pressure driving force limitation , CO2 separation, as specified, in a single stage without feed compression or permeate recycle is not feasible, irrespective of the membrane performance. As referred to earlier, Merkel et al.83,93 from

Membrane Technology and Research, Inc. recently studied a process of recycling CO2 on the feed side back to the boiler using air as sweep gas in the second membrane stage

(Figure 4.1). Combustion with air containing this recycled CO2 produces a flue gas with higher CO2 concentration. This provides a larger driving force for separation and a lower enrichment need in the first membrane stage which produces the CO2 product for sequestration. This process has shown promise to meet the economics of carbon capture and thus is well-suited as a basis to evaluate membrane performance targets. In this work, we present a detailed investigation of the two-stage process scheme using combustion air as sweep at 1 bar in the second membrane stage (Module 2 in Figure 4.1) and vacuum on the permeate side of the first membrane stage (Module 1 in Figure 4.1).

Figure 4.1 shows the process which is similar to what was proposed by Merkel et al. For the purpose of this study, the separation has been simplified to be purely membrane- based and achieve a high CO2 purity in the first stage itself so that the CO2-rich stream can be directly compressed and sequestered, thereby eliminating additional purification steps.

104

4.4 Process modeling and economics

4.4.1 Membrane process modeling and simulation

The transport of flue gas through the membrane module was simulated using a one-dimensional hollow fiber model. Molar balances can be written for each component as shown in Equations 3 and 4.

dn fi d J (4.3) dz i

dn si d J (4.4) dz i

In the Equations 3 and 4, the left hand sides represent the change of component molar flow rate with respect to position in the feed and sweep sides, respectively. The right hand sides represent the permeation through the membrane. The overall enthalpy balance for the feed side is written as:

d() nfi H fi d ( Ji H fi ) dU ( T f T s ) dz

The left hand side represents the change in feed stream enthalpy with respect to position. The first term on the right hand side represents the total enthalpy carried by the permeating components from the feed side while the second term is the heat transfer between feed and sweep sides including the conductive heat transfer through the membrane layer. The equation can be further simplified as shown below:

dHfi dn fi (nfi ) ( H fi ) d ( J i H fi ) dU ( T f T s ) dz dz

105

dH fi (nfi )( H fi d J i) d() J i H fi dU( T f T s ) dz

dH fi (n ) dU ( T T ) fidz f s

With no phase change, dHfi C pfi dT f . So, the equation can be rewritten as:

dTf dU T (4.5)

dz nCfi pfi

where ΔT = Tf – Ts. The left hand side of Equation 5 represents the change of temperature with respect to position in the feed side. The overall enthalpy balance for the sweep side can also be written similarly.

d() n H si si d ( J H ) dU ( T T ) dz i fi f s

dH (nsi ) d J ( H H ) dU ( T T ) sidz i fi si f s

The equation can be further simplified by noting dHsi C psi dT s and

HHCTTfi si psi() f s .

dU T d ( J C ) T dTs i psi ( 4. 6) dz nCsi psi

The additional term in Equation 6 compared to that in Equation 5 represents the difference in the energy carried by the permeate between leaving the feed side and 106 entering the sweep side. The Equations 3 – 6 constitute a system of ordinary differential equations similar to those discussed in Chapter 2 and in our previous work.14,73

The boundary conditions are set by known conditions at the feed and sweep inlets.

They are listed as follows:

For the first membrane stage:

At z = 0: nfCO2 = XCO2 × nto, nfN2 = XN2 × nto, nfH2O = XH2O × nto

At z = L: nsCO2 = 0, nsN2 = 0, nsH2O = 0 where nto is the molar flow rate of the stream entering the stage on the feed side. For this stage, nto, XCO2, XN2 and XH2O correspond to Stream 1 in Figure 4.1. Due to the absence of a sweep stream at a different temperature, the temperature of Stream 1 is unlikely to change with position in Stage 1. Thus, Equations 5 and 6 can be eliminated for this stage.

For the second membrane stage:

At z = 0: nfCO2 = XCO2 × nto, nfN2 = XN2 × nto, nfH2O = XH2O × nto, Tf = (273.15+57.2) = 330.4 K

At z = L:

-6 nsCO2 = 380×10 γ × nto, nsN2 = 0.782 γ × nto, nsH2O = 0.01 γ × nto, Ts = (273.15+15) =

288.15 K

For this stage; nto, XCO2, XN2, XH2O and Tf correspond to Stream 3 in Figure 4.1. γ is the sweep to feed molar flow ratio. The temperatures of the flue gas and air streams are given in Table 4.1. This system of equations was fed into the Partial Differential Equation

107

(PDE) mode of COMSOL Multiphysics which uses the finite element method to solve them. The domain (module length) as well as the dependent variables were non- dimensionalized and divided into 120 mesh elements. The result obtained was not influenced by further reduction in mesh size. The predefined element type was

Lagrange-quadratic.

The important assumptions of the model are:

1. The module operates at steady state in an adiabatic and countercurrent mode.

2. There is no axial mixing on both the lumen and shell sides; and pressure drops are

negligible.

3. The permeances remain constant along the module length. CO2, N2 and H2O are the

permeating components. In CO2-selective ( CO2/N2 > 1) membranes, water generally

has a larger permeability. However, at high CO2 permeances of >2000 GPU or so as

considered in this study, support resistances and concentration polarization are

expected to limit the transport. Thus, we have assumed H2O/CO2 = 1.

The process-related assumptions are listed below:

1. In the process shown in Figure 4.1, all the combustion air is used as sweep in the

second stage. Sweep flow is calculated assuming all the N2 in the flue gas is

contributed by the air.

2. The diluted combustion air with recycled CO2 can be used in the boiler.

3. The effect of impurities in flue gas can be ignored.

6 4. The purity of CO2 product is fixed at 95%.

108

5. A two-stage pump is chosen for evacuation since large scale single-stage pumps are

not readily available.

6. TS&M costs contribute 4% to the increase on the COE.6

It is important to note that since constant permeance is assumed in this study, the temperature changes calculated from Equations 5 and 6 do not affect the membrane area estimate and the results discussed in Section 4.5. However, this variation can be significant especially in the second membrane stage with air sweep. In that case,

Equations 4.1 – 4.6 coupled with an equation describing the change of permeance with temperature (in the Arrhenius expression) can be solved to evaluate the membrane area.

The temperature change still is useful in evaluating the possibility of water condensation when the relatively hot and moist flue gas is cooled by the sweep air in the second membrane stage.

4.4.2 Economics

The fixed parameters of the process are presented in Table 4.1. The methodology used to calculate the economic parameters of the process, outlined in Table 4.2, was obtained or adapted from previous studies.5,79,80,81,95,96,97,98,99 The terms “capture cost” and

“COE increase” are defined in Appendix A.1.

4.4.2.1 Capital cost estimation

The membrane element cost of $2/ft2 of membrane is based on the current membrane price for gas separation and water desalination applications. In the absence of feed compression, there is no need to use more expensive pressure vessels for the

109

2 2 membrane modules. Consequently, a low cost of $2.5/ft ($26.9/m ) for the membrane module (housing + element), MC, was used as the base price.

The final compression can be achieved using a combination of compressor (gas compression) and pump (liquid compression) which can reduce the total energy consumption, and also the installed equipment cost.97 It was deduced that a 95% pure

CO2 stream (CO2-N2 mixture) can exist as liquid at 27 °C if the pressure is as high as

100 85 bars. The compression of the CO2-rich permeate gas stream from 1 to 85 bars must be done in multiple stages since the compression ratio is larger than 10.79,101 Hence, a multi-stage centrifugal compressor was selected. Six stages were assumed in the calculation, which is similar to previous studies considering 5 or 6 stages .5,79,84,85,97 The

CO2 liquid at 27 °C and 85 bars is then pumped to 150 bars.

The purchase cost for the compressor-related equipment was calculated using the vendor estimates in Reference 5, and further discussed in Appendix A.2. The equipment cost index for pumps and compressors was taken from a monthly publication about chemical engineering.102 Costs of intercoolers as well as the dryer used to make the pipeline grade CO2 stream were included.

The pump purchase cost was obtained with the equation adapted by McCollum and Ogden97 from Hendriks103 and the IEA Greenhouse Gas R&D Programme Report.104

1.11 E Pump Cost in $ million p 0.07 (4.7) 1000 where Ep is the energy consumption of the pump.

110

The purchase cost of the vacuum pump was estimated using the industrial average of $500/kW of power required.83

The purchase cost of the flue gas and air blowers was estimated using data from the Matches Company 98 and Equation 8. Since the flow rates of the above streams are much larger than what the largest blowers can handle, multiple blowers are required. So, the scale-up factor m was taken as 1.

m Inflation Index2 Size2 Cost 2 Cost1 (4.8) Inflation Index1 Size1

The after-cooler for the CO2 compressor, the intercooler/intercondenser of the vacuum pump and its after-condenser were all assumed to be water-cooled. The areas of the heat exchangers were calculated using the overall design heat transfer coefficients given by Kern.105 The purchase costs were then estimated using the online tool for process economics developed by Peters et al.106 and Equation 8. The purchase cost

(corresponding to 2010 U.S. dollars) was estimated using the chemical engineering plant cost index.102

For all the non-membrane equipment items described above, an installation cost of 45% of the purchase cost was added.99

4.4.2.2 Operating cost estimation

The efficiency of the compressors and blowers was taken to be 85% in agreement with previous engineering studies.5,79,84,86,101,107 The energy consumption of each stage in the CO2 compressor, blowers and vacuum pumps, was evaluated using the following

108 equation given by Mohitpour , which takes into account the compressibility of CO2.

111

ai 1 ai ai RT P2 Zave Qc 1 ai 1 P1 (4.9) E c η 1000 c

where Ec is the energy consumption of the compressor/blower/vacuum pump, Zave is the average compressibility of CO2, Qc is the molar flow rate of the gas through the device, ai is the adiabatic index, R is the universal gas constant, T is the inlet absolute temperature of the gas, P1 is the inlet pressure, P2 is the outlet pressure, and ηc is the efficiency of compression (isentropic efficiency × mechanical efficiency).

An online source was used to determine the compressibility factor and other physical properties of the gases.109 The vacuum pump efficiency is typically less than the compressor efficiency84,85,110, and was taken to be 75%. The energy consumption of the blowers for air and flue gas streams was calculated assuming a 5% pressure increase.

The energy consumption of the pump (for liquids) was estimated using the expression given by Vogelesang.111

Qp p Ep ηp 36 (4.10)

where Qp is the liquid volumetric flow rate to the pump, Δp is the pump head, and ηp is the pump efficiency which was taken as 85%.

The make-up power is calculated by adding the energy (electricity) consumption of all the above separation and compression (SAC) facility equipment (blowers, vacuum 112 pumps, compressors, and liquid pumps) along with the auxiliary power increase in the power plant. A value of $0.05/kWh for the cost of make-up power was deduced from the numbers based on the DOE report.5 The details are further discussed in Appendices A.3 and A.4. The validity of the cost model in Table 4.2 is shown in Appendix A.5 by applying it to numbers obtained from the DOE study for the SOTA amine process.5

The cooling water requirement of the water-cooled heat exchangers and condensers was calculated using the make-up rate estimation technique outlined in

Reference 5. The make-up rate for the cooling tower is calculated as a small proportion of the circulating cooling water flow rate. Blowdown, evaporative and drift losses can be estimated separately based on the total circulating flow, and then added together to obtain the required make-up water flow rate. The cooling water load for the SAC facility was based on the amount of circulating water contributed by the associated water-cooled heat exchangers.

4.4.2.3 Annualized cost of capture and increase on the cost of electricity

The total plant investment was annualized using a capital recovery factor of

12.5% as used by Geisbrecht.80 The annualized cost of capture (including separation, compression and TS&M costs) was then added to the annual cost of the base plant

($0.065/kWh-net × net kWh produced annually) to calculate the annual cost of the plant with capture. This increased annual cost was then normalized to the net power output to determine the new COE and with that the COE increase and capture cost.

4.5 Cost sensitivity

113

Figure 4.2 shows a schematic representation of the cost-sensitivity calculation procedure. The steps involved are detailed in Appendix A.6. The process and membrane variables and their respective ranges considered for the sensitivity analysis are described below:

1. The CO2 concentration before the first stage, XCO2 was varied from 18.5% to 25%

(18.5%, 20%, 22.5%, and 25%). The increased concentration with respect to original

flue gas (~13%) is obtained by recycle in the second membrane stage.

2. Except for the results reported in Sub-sections 4.5.5 and 4.5.6, all calculations were

performed without feed compression, i.e., a pf of 1 bar.

3. It is important to note that a ps < 0.2 bar might not be practically relevant. Therefore,

the base ps was set at 0.2 bar. In some simulations, ps was obtained as an output as

discussed in the next paragraph. For the second stage, the sweep side pressure was

held at 1 bar.

4. The CO2/N2 selectivity was varied from close to 50 – 100 to about 600 or 700 while

the CO2 permeance was varied from 1000 GPU to 12000 GPU. The CO2 permeance

was fixed at 3000 GPU for some of the calculations. In order to look at the effect of

selectivity, we varied the permeate pressure while keeping the CO2 recovery (90 ±

0.05% CO2) and CO2 purity (95 ± 0.05% CO2 on dry basis) same. This means that

the permeate pressure (at a pf of 1 bar) required to just attain a desired purity

increases as the selectivity increases, and it was obtained by trial and error. In some

cases where the pressure ratio was fixed, the selectivity could be obtained by similar

114

trial and error. Appendix A.6 contains additional details about this method and the

associated uncertainty in the output.

4.5.1 Effect of CO2 concentration before the first stage

Table 4.3 shows the variation of overall costs and required membrane selectivity with increasing XCO2 for a CO2 permeance of 3000 GPU, a feed pressure of 1 bar and ps =

0.2 bar. The required selectivity increases from 115 to 430 as the CO2 concentration before the first stage reduces from 25% to 18.5%. This is due to the fact that enrichment needed (for 95% CO2 on dry basis) is higher at a lower concentration. Also, as shown in

Figure 4.3, the first-stage membrane area required to achieve a desired CO2 recovery increases as XCO2 reduces, leading to a greater net transport of N2 to the permeate side.

To decrease this transport and achieve the necessary enrichment while maintaining a desired purity necessitates a higher selectivity. On the other hand, at a given selectivity, the vacuum requirements for the first membrane stage will go down with increasing XCO2, resulting in energy savings. This effect has been systematically explored in the case of single stage processes.84,85,89

The membrane area shows a more intricate relationship with the CO2 concentration. As shown in Figure 4.3, the first-stage membrane area drops with increasing CO2 concentration mainly due to the greater driving force. At the same time, the second-stage area increases. This is due to the fact that more CO2 must be recovered in the second stage as XCO2 increases. Due to these opposing effects, the variation in the total membrane area is relatively small. Consequently, the variation in the overall costs is

115 also small. The important variation is therefore the reduced selectivity requirement at higher concentration.

However, it is worth remembering that the selectivity required will also be governed by the O2 concentration in the air stream entering the boiler. The O2 concentration will reduce with increasing CO2 concentration due to the dilution of air caused by the recycled CO2. Also, if the membrane selectivity is low and the second- stage membrane area is high, O2 will permeate more to the feed side in the second stage, leading to a further reduction of O2 concentration in the boiler air. Due to these reasons, increasing the CO2 concentration beyond 20 – 22.5% may not be practical.

Finally, the water fraction of the permeate stream reduces from about 47% to 40% when XCO2 increases from 18.5% to 25%. This is a direct result of the reduced membrane area and the fact that the water concentration in the feed stream is constant at about 17%

(saturated at 57 °C) irrespective of the CO2 concentration. This water concentration, which depends on the flue gas temperature, can influence the amount of water permeation in Stage 1 and affect the membrane area. However, for the purpose of this study, the water concentration and temperature have been kept constant.

4.5.2 Effect of CO2/N2 selectivity

Higher selectivity reduces energy consumption (by decreasing the vacuum or increasing ps to achieve 95% CO2 purity) as shown in Figure 4.4. This can be attributed to a simultaneous reduction in pressure ratio, also shown in Figure 4.4. The pressure ratio, pf/ps, decreases from 20 (1/0.05) to about 3.5 (1/0.285) when the selectivity increases from about 80 to 500. A closer look reveals that most of the change takes place

116 at a selectivity <160 (base ps = 0.2 bar, pf/ps = 5). Since a permeate pressure of <0.2 bar is considered impractical, a selectivity of <160 or so can be considered inadequate for the above process operating at a feed pressure of 1 bar. The energy consumption at this point is about 0.19 MWh/ton CO2 (<15% of total plant power output), which is significantly lower than that of the SOTA amine process (0.37 MWh/ton CO2 [10], about 29% of the total plant output).

Figure 4.4 also shows that the separation energy reduces by about 60% during this change (selectivity from 80 to 500) while the reduction in the total energy consumption of the process (separation + compression) is lower at about 35%. At a selectivity of

>160, the reductions in both are smaller at about 20% in the former and 8% in the latter, respectively. It is important to note that the pressure ratio affects only the vacuum pump energy which accounts for about 70% of the separation energy and roughly 30% of the overall energy.

The annualized non-membrane cost (without TS&M cost) is a strong function of the energy consumption so that it follows a similar trend with selectivity as shown in

Figure 4.4. As indicated in Appendix A.3, it has two components. The first component associated with the increased fuel costs, and the larger size of the power plant with capture (excluding the SAC facility) accounts for 55 – 60% of the annualized non- membrane cost while the remaining is accounted by the equipment capital costs (other than membrane) and operating costs of labor and cooling water related to the SAC facility.

117

The total membrane area increases linearly with selectivity as shown in Figure

4.5; this is due to the increase in the first-stage membrane area. The pressure ratios corresponding to different selectivities are the same as in Figure 4.4. As the pressure ratio reduces at higher selectivities, it decreases the driving force to just attain the desired purity, which can in turn increase the membrane area significantly in a regime of a limited pressure ratio (about 5 – 10). Merkel et al. recently emphasized the effect of increased selectivity on membrane area at a constant pressure ratio.83 In this work, the membrane area increase is expected to be higher due to the corresponding decrease in the pressure ratio.

The opposing effects of selectivity on energy consumption and membrane area suggest that there is a cost-selectivity trade-off, which is depicted in Figure 4.6. At XCO2 =

22.5% (the pressure ratio-selectivity relationship is the same as that in Figure 4.4), the variation in the overall cost is relatively small beyond ps = 0.2 bar and a selectivity of about 160 while at XCO2 = 20% (the pressure ratios corresponding to different selectivities are given in the figure caption), a similar change occurs beyond a selectivity of about

275. The minimum costs are shown in Table 4.3. At a higher membrane price of $4/ft2 and XCO2 = 22.5%, the cost follows the same trend with selectivity, with the drop (for a selectivity increase of 80 to 160) being somewhat smaller on an absolute basis. This variation is due to the difference in relative contributions of membrane and non- membrane costs to the overall cost at different membrane prices.

4.5.3 Effect of CO2 permeance

118

Figure 4.5 also shows how the required membrane area reduces at higher permeance. As a result of this, the cost of electricity increase could go down to ~27% at

12000 GPU as shown in Figure 4.7 at a selectivity of about 160, pf = 1 bar and ps = 0.2

112 bar. At 1850 GPU (close to the highest reported in the literature ) and XCO2 = 22.5%, the COE increase is about 38.5% with a capture cost of $27.6/ton CO2 while at 3000

GPU and XCO2 = 22.5%, the COE increase is 33.4% with a capture cost of $24/ton CO2.

But, it is important to note that at 1850 GPU, the reported selectivity was about 55 at around ambient temperature.112 Also, for that case, the permeance at 1 atm was measured in single gas experiments without sweep gas and then used to obtain the selectivity. At a selectivity of 55 and other conditions kept same as that in Figure 4.7, the permeate CO2 purity is only about 85%. In order to achieve 95% purity in the CO2 product, the pressure ratio has to be increased which is likely to push the COE increase to 50 – 60%, making the process economically unfavorable. In Figure 4.6, it can be seen that the COE increase at a selectivity of 80 is close to 45% even with a CO2 permeance of 3000 GPU. Thus, at current membrane performance, the costs are too high (50 – 60% COE increase) to achieve the targets using a purely membrane-based air-sweep process.

Figure 4.7 also shows that the cost reduction slows down at higher permeance.

From the cost contributions shown in Figs. 4 and 5, it is deduced that the membrane accounts for about 10 – 15% of the total annualized cost at 6000 GPU while this contribution increases to 20 – 30% at 3000 GPU. This explains why the effect of membrane area reduction diminishes as permeance increases. By comparing Figs. 6 and

7, it is interesting to note that the COE increase reduces from 43.9% to 33.4% when the

119 selectivity increases from ~80 to 160 while a permeance increase from 1500 GPU to

3000 GPU gives rise to a comparable drop in the costs (from about 43 – 44 % to 33.4%

COE increase). This observation may seem different from that of Merkel et al.83 whose study revealed that increase in selectivity beyond 50 is far less important than increase in permeance beyond 1000 GPU. This difference arises mainly from the difference in the

CO2 purity achieved (on dry basis) after the first membrane stage (95% in this study vs.

83% at 2 bar feed pressure and <80% at 1 bar feed pressure in Merkel et al.‟s study).

These differences are further discussed in Section 4.5.7.

4.5.4 Vacuum pump efficiency

In a membrane-based process, most of the energy consumption of the separation step is contributed by the vacuum pump. Vacuum pumps are typically less efficient than compressors.84,85,110 Although an efficiency of 75% is assumed by this study, it is worthwhile to look at how sensitive the overall costs are to a drop in this efficiency. The vacuum pump contributes close to 70% of the energy consumed by the separation step for the case shown in Figure 4.4. For this case, the separation step contributes about 32% of the total energy consumption of the SAC facility. From the cost contributions shown in

Figures 4.4 and 4.5, it is deduced that a 5% drop in efficiency could lead to about 1.5% rise on the COE increase.

4.5.5 Effect of feed pressure

The effect of feed pressure on the costs was investigated for a CO2 permeance of

3000 GPU, XCO2 = 22.5% along with a CO2/N2 selectivity of about 160. As shown in

Figure 4.8, at close to 1.1 bar, the COE increase is the lowest at about 33% with a capture

120 cost of $23.5/ton CO2. These numbers are almost same as those at a pf = 1 bar. As the feed pressure increases over 1 bar, the compression costs increase but the membrane- related costs decrease systematically due to a reduction of the required area. As the feed pressure increases, the membrane area reduction becomes less prominent than the increase in compression costs, and the optimum lies close to 1 bar. It is worthwhile to note that the required selectivity reduces with an increase in the feed pressure. At pf = 1.3 bars, the required selectivity is about 120 vs. 160 at pf = 1 bar. This is because of the increase in pressure ratio at the same ps = 0.2 bar from 1/0.2 = 5 to 1.3/0.2 = 6.5. Due to the same reason, the required selectivity reduces from 275 at pf = 1 bar to about 175 at pf

= 1.3 bars for XCO2 = 20%.

From the results shown in Figure 4.8 and from the discussion in Sections 4.5.1 to

4.5.4, we can conclude that a selectivity of 145 is close to the minimum required at a

XCO2 = 22.5% with a reasonable pressure ratio that can meet the cost targets.

4.5.6 Effect of membrane price on cost vs. feed pressure

The effect of membrane price on the relation between cost and feed pressure is shown in Figure 4.9. As membrane price increases, the overall costs increase as shown by the difference in the curves in this figure. Since area reduction becomes more important at higher membrane price, the optimum feed pressure shifts toward a higher value, for instance close to 1.3 bars at $10/ft2 of membrane element cost. Conversely, the optimum feed pressure approaches 1 bar as the membrane element cost reduces. This effect is due to the change in the contribution of the membrane related cost to the total cost.

121

For the effects discussed in Sub-sections 4.5.5 and 4.5.6, the membrane price is assumed to be independent of the feed pressure. In reality, the membrane price might increase at higher pressures due to increase in the cost of the module. This would push the optimum closer to atmospheric feed pressure. Another assumption implied in Sub- sections 4.5.5 and 4.5.6 is the absence of pressure recovery. At higher feed pressures, pressure recovery would be more useful in reducing the compression energy penalty which could push the optimum somewhat away from a pf = 1 bar. In general, at low enough membrane unit prices and high enough CO2 permeance, membrane cost contribution to the overall cost is relatively small as indicated in Figure 4.8 due to which lower feed pressures are preferred from an energy consumption viewpoint. These effects have also been studied in detail by Merkel et al.83 However, they arrived at an optimum pressure of 2 bars for the process. This can be attributed to the differences in the estimation of the non-membrane costs which are explained in Section 4.5.7.

4.5.7 Comparison with literature

The work at Membrane Technology and Research, Inc.83 has successfully shown the potential of air-sweep process in achieving the cost targets of the above application.

Their work also showed the sensitivity of the costs to the feed pressure, membrane selectivity and permeance. The important conclusion was that at a feed pressure of 2 bars, a CO2 permeance of 1000 GPU and a CO2/N2 selectivity of 50, the air-sweep process could reduce the capture costs to $23/ton CO2. These conclusions might seem to be drastically different from the findings reported in this chapter. Therefore, it is important to look at the differences between the two studies. Table 4.4 gives a quick

122 comparison between the two studies with respect to the most important parameters/assumptions.

The first four parameters shown in Table 4.4 are close to the same in both the studies. The parameters 5 and 6 are different but as shown in the analysis in Sections

4.5.1 to 4.5.6, the costs rise rapidly at much lower permeances (1000 GPU or so) or higher membrane prices ($4.5/ft2 which is close to $50/m2). These considerations coupled with the fact that Merkel et al. found 2 bars as the optimum feed pressure mean that our study predicts significantly higher non-membrane costs. Parameters 9 and 10 explain some of the differences in this respect. In the current study, we devised a systematic way of calculating the make-up power cost (MuPC) which is an important parameter in cost estimation. This method, which is explained in Appendix A.3, uses the detailed DOE study5 to estimate MuPC by comparison with the amine process.

Parameter 10 which is also obtained from the DOE study is even more important since it decides the flue gas flow rate. It can directly influence the fraction of power produced at the plant used for CO2 capture and thus reduce the net power output. This penalty is somewhat ignored when capture cost ($/ton CO2) is used as a cost metric since it normalizes the total costs to the total amount of CO2 captured (proportional to gross power and not net power output). We use a better metric, “% COE increase” as recommended by DOE for cost comparisons. Also, the cost methodology presented

(Table 4.2) is more detailed with respect to the non-membrane costs other than energy- related costs and has been compared and verified with the DOE estimates for the amine process (Appendix A.5).

123

Lastly, the difference in Parameter 7 shows why higher selectivity was required in the present work. We assumed that a CO2 stream of 95% purity can be generated by the membrane process itself so that any subsequent separation could be avoided. Merkel et al. used compression and cryogenic enrichment to increase the CO2 purity from 83% to

>95% and make supercritical CO2. The energy consumption mentioned (36 MW) they reported is very close to the compression energy (at 80% isentropic efficiency assumed by Merkel et al. for six stages) from 1 bar to 140 bars for a pure CO2 stream at 90% recovery. It does not seem to include any energy penalty in enriching the 83% pure CO2 stream to a purer supercritical state.

4.6 Conclusions

1) By using a detailed cost-sensitivity analysis, this study shows the membrane

performance and conditions under which the purely membrane-based air sweep

process can meet the DOE capture goals.

2) High CO2 permeance, low membrane cost and close to atmospheric pressure

operation are the key requirements to achieve the DOE cost targets.

3) At a low membrane price of $2.5/ft2 (~$27/m2), the purely membrane-based air-

sweep process can result in a COE increase of <35%, down to 33%, and a capture

cost of <$24/ton CO2 at a CO2 permeance of 3000 GPU, a CO2/N2 selectivity of

about 150 and a feed pressure of close to 1 bar.

4) To achieve the cost goals for the process configuration studied, the membrane

CO2/N2 selectivity must be higher than that reported in the literature for high-

124

83,112 permeance polymeric membranes which is typically close to 50 for a CO2

permeance of 1000 GPU – 2000 GPU. A higher CO2/N2 selectivity decreases energy

requirements significantly due to the higher permeate pressure in the first membrane

stage. But, increasing selectivity indefinitely is not beneficial due to the associated

rise in membrane area.

5) At a CO2 permeance of 1850 GPU and a CO2/N2 selectivity of 55 as in Reference 112

and other conditions kept same as that in Figure 4.7, the permeate CO2 purity is only

about 85%. In order to achieve 95% purity in the CO2 product, the pressure ratio has

to be increased which is likely to push the COE increase to 50 – 60%, making the

process economically unfavorable. Further improvement in membrane performance

is thus crucial to finding a purely membrane-based technology for this application.

Acknowledgements

The authors would like to thank the National Science Foundation, the Office of Naval

Research (N00014-11-C-0062), the Department of Energy/National Energy Technology

Laboratory (DE-FE0007632), and The Ohio State University for the financial support of this work. Part of this material is based upon work supported by the National Science

Foundation under Grant No. CBET 1033131 and IIP 1127812. This work was partly supported by the Department of Energy under Award Number DE-FE0007632 with substantial involvement of the National Energy Technology Laboratory, Pittsburgh, PA,

USA.

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Table 4.1. Fixed parameters in the cost calculation.5,6,79,81 *This is the composition at the exit of the desulfurization unit. Component molar flow rates of O2 and SO2 were assumed

to remain constant along the length of the membrane module.

* Flue gas composition 13.2% CO2, 17.3% H2O, 67.2% N2, 2.3% O2 , 38 ppm SO2 Temperature 57.2 °C CO2 emission rate in raw flue gas 472 metric tons/hr (1 metric ton = 1000 kg) Original or base power plant 550 MWe pulverized coal-based CO2 recovery (%) 90 CO2 purity in product (%) 95

Combustion air for sweep Regular air at 15 °C and 1 bar with 79% N2, 21% O2 and 380 ppm CO2 by volume on dry basis, 60% relative humidity (1%)

126

Table 4.2. Methodology to calculate economic parameters for the process.

5,79,80,81,95,96,97,98,99 1 US gallon = 3.785 liters. This unit make-up power cost was evaluated

using numbers from Reference 5 as explained in Appendix A.3.

Total plant investment (TPI) Total membrane module cost (MC) $2.5/ft2 ($26.9/m2 includes the membrane element) Installed compressor and pump cost (CC) CC (described below) Installed blower cost (BC) BC (described below) Installed vacuum pump cost (VPC) VPC (described below) Installed heat exchanger cost (HC) HC (described below) Fixed cost (FC) MC+CC+BC+VPC+HC Base plant cost (BPC) 1.12 FC Project contingency (PC) 0.20×BPC Total facilities investment (TFI) BPC+PC Start-up cost (SC): 0.10×VOM TPI TFI+SC Annual variable operating and maintenance cost (VOM)

Contract and material maintenance cost (CMC) 0.05×TFI Local taxes and insurance (LTI) 0.015×TFI Direct labor cost (DL) $15/hr (based on 8 h/day per 366 mole/s of feed) Labor overhead cost (LOC) 1.15×DL Membrane element or replacement cost $2/ft2 of membrane (MRC) Cooling water cost (WC) $1.08/1000 US gallons Make-up power cost (MuPC) $0.05/kWh Energy consumption EC (kWh) VOM CMC+LTI+DL+LOC+MRC+WC+MuPC×EC 0.125×TPI Annual capital related cost (CRC) VOM+CRC Annualized Cost (AC)

Other assumptions

Membrane life 4 years On-stream factor (OSF) 85% Base cost of electricity $0.065/kWh-net (original power plant without capture, 2010 dollars) (COE)

127

Table 4.3. Effect of CO2 concentration before the first stage on overall costs for a CO2

permeance of 3000 GPU, pf of 1 bar and ps of 0.2 bar.

Optimum CO2/N2 COE Increase Capture Cost

XCO2 Selectivity (%) ($/ton CO2)

18.5 430 34.4 24.6

20.0 275 33.5 23.9

22.5 163 33.4 24.0

25.0 115 34.1 24.5

128

Table 4.4. Comparison of current work with that by Merkel et al.83

Parameter/Assumption Merkel et al. Current work

1 Permeate pressure 0.2 bar 0.2 bar

2 Water permeation Yes Yes

3 Recycled CO2 concentration 18 – 20% 18.5 – 25%

4 CO2 purity >95% 95%

5 CO2 permeance 1000 GPU 3000 GPU

6 Membrane module cost $50/m2 $27/m2

7 CO2 purity after first stage (dry basis) 83% 95%

8 Feed pressure 2 bars 1 – 1.3 bars

9 Make-up power cost $0.04/kWh $0.05/kWh

10 CO2 flow rate (550 MW power plant) 372 tons/hr 472 tons/hr

11 Cost metrics Capture cost COE, capture cost

129

Membrane Air Stream Membrane Module 2 With CO2 Module 1 Air (5) Flue Gas Treated

(4) (1) (3) Flue Gas

(2) Vacuum Coal Pump Combustor Compressor

2200 psia Coal Feed

Figure 4.1. Membrane process using combustion air as sweep

(feed compressor/blower, pumps and heat exchangers are not shown).

The numbers in parentheses indicate streams.

130

(Concentration before the first stage, Flue gas composition before CO2 recycle, Temperature, Air stream flow rate)

Overall Mass Balance (Streams 1, 2, 4 and 5)

Streams 1, 2;

Membrane parameters, Pressures Cost

Stage 1 Membrane Calculation

Simulation Spreadsheet Streams 4, 5 (90% Recovery, 95% Membrane area,

Purity) permeate pressure

Stream 3 Membrane area

Stage 2 Membrane Simulation

Figure 4.2. Schematic of cost-sensitivity calculation procedure.

131

2.0

Total

) 1.5 2 Second stage

1.0

0.5 First stage Membrane Area Area (m Membrane

0.0 16 18 20 22 24 26 28 CO Concentration before First Stage (%) 2

Figure 4.3. The variation of membrane area with CO2 concentration before the first stage for a CO2 permeance of 3000 GPU, pf = 1 bar and ps = 0.2 bar. This plot corresponds to

the data shown in Table 4.3.

132

0.30 )

2 90

0.25 80 70 0.20 60

pf/ps = 20

Total Energy membrane Cost

50 - 0.15 p /p = 8.6 f s 40 million)($ Separation Energy 0.10 pf/ps = 5 pf/ps = 4.5 30 pf/ps = 3.9 pf/ps = 3.6 pf/ps = 3.5 20 0.05

10 AnnualizedNon Energy Consumption (MWh/tonCO Consumption Energy 0.00 0 50 150 250 350 450 550 Selectivity

Figure 4.4. The effects of CO2/N2 selectivity on energy consumption and annualized non-

membrane cost for XCO2 = 22.5%. This figure also implies that energy consumption is independent of the CO2 permeance. At a CO2/N2 selectivity of about 160 and pf = 1 bar,

pf/ps = 5.

133

4 40 ) 2 35 3000 GPU 3 30

2 3000 GPU 20

15 million) ($

1 10

6000 GPU Membrane Area (million m (million Area Membrane 5 Cost Membrane Annualized

0 0 50 150 250 350 450 550 Selectivity

Figure 4.5. The effects of CO2/N2 selectivity on membrane area and annualized

membrane cost for XCO2 = 22.5%. The annualized membrane cost shown on the

secondary y-axis corresponds to a CO2 permeance of 3000 GPU and pf = 1 bar.

134

2 45 22.5% CO2,$4/ft

40 2 20.0% CO2,$2/ft 35

2 30 22.5% CO2,$2/ft

Cost of Electricity Increase (%) (%) Increase Electricity of Cost 25

20 50 150 250 350 450 550 650

Selectivity

4.4, 4.2 and 4.1, respectively. At the same pressure ratio, the selectivity required is

higher for 20.0% CO2.

135

70 40 )

35 2 60

30 50 25 40 20

15 Cost Capture ($/tonCO Cost of Electricity Increase (%) Increase (%) Electricity of Cost 20 10 0 3000 6000 9000 12000

Permeance (GPU)

Figure 4.7. The effects of CO2 permeance on overall costs for XCO2 = 22.5% at a CO2/N2

selectivity of 163, pf = 1 bar and ps = 0.2 bar.

136

200 60

αCO2/N2 = 93

150

αCO2/N2 = 108 αCO2/N2 = 121 40

αCO2/N2 = 163 αCO2/N2 = 130

100 αCO2/N2 = 145

Cost ($ Million)($ Cost Non-membrane Cost 20

50 Cost of Electricity Increaseof Cost (%) Membrane Cost

0 0 0.5 1 1.5 2 2.5 Feed Pressure (atm)

Figure 4.8. The effects of feed pressure on overall costs for XCO2 = 22.5%, a CO2

2 permeance of 3000 GPU, ps = 0.2 bar and the membrane module price at $2.5/ft .

137

2 60 $10/ft

50 $6/ft2

40 $2/ft2

30 Cost of Electricity Increase (%) Increase (%) Electricity of Cost The optimum feed pressure approaches 1 atm 20 0.5 1 1.5 2 2.5

Feed Pressure (atm)

Figure 4.9. The effect of feed pressure on COE increase at three different membrane

element prices for XCO2 = 22.5%, ps = 0.2 bar and a CO2 permeance of 3000 GPU.

For the element prices of $2/ft2, $6/ft2, and $10/ft2, the membrane module prices

were $2.5/ft2, $6.5/ft2, and $10.5/ft2, respectively.

138

CHAPTER 5

DEPOSITION OF ZEOLITE-BASED PARTICULATE LAYERS

ON POLYMER SUPPORTS FOR CO2 CAPTURE

5.1 Summary

Membranes, due to their smaller footprint and potentially lower energy consumption than the amine process, offer a promising route for PCC. In this context, zeolite Y based inorganic selective layers offer a favorable combination of CO2 permeance and CO2/N2 selectivity, the membrane properties crucial to the economics. In order to produce thin high-flux zeolite membranes, they have been traditionally supported on inorganic supports. These inorganic supports are expensive and difficult to manufacture in a high surface area/volume configuration (hollow-fiber or spiral-wound) due to their brittle nature. We therefore propose to use flexible and scalable polymer supports to harness the potential benefits of zeolite-based selective layers. It is also possible to use such inorganic/polymer multilayer structures as novel high performance substrates for polymer membranes/selective layers.

Developing a scalable methodology for deposition of zeolite particles on polymer supports is the focus of this work. The polymer supports are rougher and also considerably thinner than most of the conventional inorganic supports. In addition, they

139 can exhibit low adhesion to the inorganic particles. The layer itself has to be thin (<1 μm) to reduce the possibility of flex-crack formation and eliminate unwanted transport resistances. These considerations pose significant challenges to the coating process. The work described below developed a detailed protocol for depositing thin zeolite Y seed layers (~40 and ~200 nm particle sizes) on polymer supports. In this work, we also studied the effects of support surface morphology (pore size and surface porosity) on the quality of deposition and identified favorable supports for the coating.

In order to obtain a complete surface coverage of the zeolite particles on the support surface with minimum defects and in a reproducible manner, a vacuum-assisted dip-coating apparatus was set-up and used. The surface coverage was complete as suggested by the presence of color patterns on the coated surface and electron microscopy images and the particulate layer was dense with some drying cracks. In order to reduce the drying cracks, thickness of the layer was reduced by decreasing the concentration of the aqueous inorganic dispersion for the smaller (~40 nm) zeolite particles. Lastly, transport characterization was used as an additional tool to study these layers.

5.2 Introduction

High performance membranes based on novel materials offer one of the few potential means of meeting the stringent economics of PCC. Membranes, both polymeric and inorganic have been researched for this application. These membranes usually consist of a thin selective layer (nm to μm in thickness) supported on a porous and relatively

140 thicker support for mechanical stability forming an anisotropic multilayer composite structure.112,113,114,115 Polymeric membranes (mechanisms (a) and (b) in Figure 3.1) are flexible and scalable in the form of hollow-fiber and spiral-wound modules having high surface area/volume ratios. Although some polymer membranes based on polar ethylene oxide (EO) groups in the backbone have demonstrated high CO2 permeance (>2000

GPU)83,112, their performance is usually limited by the Robeson‟s upper bound or the selectivity-permeability trade-off.53 Inorganic membranes (mechanism (c) in Figure 3.1) on the other hand can potentially provide a higher selectivity at a comparable permeance113,116,117 but are plagued by irreproducibility due to defects and the use of thick, brittle, less scalable, less compact and more expensive inorganic supports.118,119,120

The support cost issues especially have so much hindered the development of inorganic thin film composite membranes that barring a few examples119, there has been no commercialization. If these issues are not resolved, commercializing an inorganic membrane for a gas separation application of this scale seems impractical.

As a potential solution to the above problem and to harness the performance benefits of inorganic membranes for CO2/N2 separation, we studied appropriate porous polymer membranes as supports for promising zeolite-based inorganic layers. These porous membranes which are generally made by phase inversion have traditionally been used in ultrafiltration, microfiltration and as polymer membrane supports. Common polymers are polysulfone (PSf), polyethersulfone (PES), polyacrylonitrile, cellulose acetate, nylon, etc. Since such supports have not yet been studied for inorganic selective layers or even inorganic particulate layers, our focus was to establish a protocol and

141 develop a scalable method for depositing stable zeolite Y particulate layers with minimum defects on such supports. The specific goals of this work have been summarized below:

1. Study and identify different support materials and support morphologies that will

allow us to make defect-free zeolite Y layers for the above application.

2. Focus on fabricating ultra-thin layers 0.5 – 1 μm in thickness with almost no

micro-cracks, pin-holes and defects.

In order to grow zeolite Y-based selective layers from the deposited zeolite Y seed layers, there is ongoing collaboration with Dr. Prabir Dutta‟s group in the Chemistry

Department. They also provided the lab-synthesized zeolite particles for this work. Those aspects won‟t be a part of the work presented in this dissertation. However, we coated the zeolite particulate layers with a defect abatement polydimethylsiloxane (PDMS) layer and analyzed their separation performance which is discussed in Section 5.5.3.

5.3 Background and rationale

5.3.1 Zeolite Y as membrane material

Zeolites are crystalline aluminosilicates with well-defined microporosity. The inherent pores in these materials are formed by different spatial arrangements of silicon and aluminum atoms along with oxygen anions. The size of pores in zeolites is of the molecular scale which gives them the ability to interact with matter at that level. This quality has enabled their applications in a wide variety of fields like catalysis, separations, detergency and chemical sensing.121 From a separation point of view,

142 zeolites are often called molecular sieves due to their fixed pore sizes that can distinguish between molecules of different shapes and sizes. Also, depending upon the Si/Al ratio and the number of neutralizing cations inside the pores, zeolites can have different adsorptive properties, with the hydrophobicity increasing as the Si content increases.54,121

Traditionally, zeolites have been used in adsorptive processes.

Membranes are interesting from the point of view of using these materials in a continuous separation process. The CO2 and N2 molecules are similar in their kinetic sizes at 3.3 Å and 3.6 Å, respectively.53 Hence, pure size-sieving is not expected to yield high selectivities. Additionally, smaller the pore size, higher is the resistance to diffusion due to which the permeances obtained via pure molecular sieving are generally lower.54

Hence, bigger pores are preferred.

Membrane permeance also depends on the thermodynamic adsorption strength of the molecule on the zeolite pore surface in addition to the kinetic diffusion barrier. If the pore size is too large for molecular differentiation, separation can still occur if the material can preferentially adsorb one of the molecules on its surface. In this case, depending upon the extent of affinity, adsorbed molecule could preferentially diffuse along a concentration gradient on the surface by the so-called, “surface diffusion” mechanism (Figure 3.1).54,122 The pore area available for the less-adsorptive molecule is then effectively reduced or, in some cases, it could even be blocked. The quadrupole moment of the CO2 molecule is about three times and polarizability about twice that of

54,123 the N2 molecule. Also, CO2 is more condensable than N2 (critical temperatures: CO2:

55 304.1 K, N2: 126.2 K) . It can therefore interact selectively with the zeolite surface.

143

Zeolite Y because of its pore size of about 7 Å, is one of the interesting candidates for the above separation. Figure 5.1 shows the cage structure of zeolite Y. The cage size is large enough to not have unwanted interaction with the framework. Molecular

Dynamics simulations have indicated that pure zeolite Y crystal permeability could be

5 >10 Barrers with a CO2/N2 selectivity of greater than 200 at typical flue gas operating conditions54, which is the highest predicted performance among all zeolites. These values are comfortably above the Robeson upper bound for polymeric materials.54,53

Experimentally, White et al. obtained extremely high selectivities of greater than 500 at a

114 permeance of 300 GPU using a Zeolite Y membrane on alumina support. CO2 permeances of greater than 2000 GPU at CO2/N2 selectivities ~50 have been achieved using even smaller pore117 or higher Si/Al ratio zeolites.116 In order to make a zeolite membrane, the zeolite crystals must all be connected in a thin film of polycrystalline structure. The performance values predicted by simulations have not been achieved experimentally, in part due to the difficulties in making a defect-free and continuous polycrystalline structure. Defects can reduce the selectivity by allowing non-selective convective gas flow through them although new approaches like coating an inorganic layer with PDMS have been successful in plugging defects in inorganic membranes.124

5.3.2 Zeolite membrane synthesis

Polycrystalline zeolite layers for membrane applications are generally fabricated by the deposition of a seed layer of zeolite particles or nuclei (in the nm – μm range) on a porous support followed by secondary growth of the seed layer to eliminate the

144 interzeolitic pores.125 Other less successful methods are the direct or in-situ hydrothermal synthesis of a zeolite film on a substrate and embedded method.126

White et al. dip-coated a ~200 nm zeolite Y suspension in water onto a porous alumina support to obtain a 1.6 µm thick zeolite seed layer.114 The suspension was stable without any polymer or dispersant. In the second step, the dried seed layer was subjected to secondary growth for seven days in the presence of an alkaline growth solution at a temperature of around 373 K. One of the larger goals of this work is to synthesize a similar selective layer on polymer supports. The focus of this chapter will be the first step, the deposition of zeolite particles on such supports.

The particulate layer deposited in this work can also be used as a gutter layer between the polymer support and a polymeric selective layer. In this case, the particulate layer can provide a means of obtaining a more uniformly porous substrate with a pore size that can be changed easily by varying the particle size. Synthesis of nanozeolites of different sizes has received considerable attention for different applications. They are therefore, a natural choice for use as substrates too. This „polymer/inorganic substrate‟ approach has its advantages over the purely polymeric approach commonly used in commercial polymer membranes, especially for the transport of highly permeable molecules. This will be discussed in greater detail in Chapter 6.

5.3.3 Seed layer deposition

It is imperative to obtain defect-free and crack-free seed layers from stable colloidal dispersions of zeolite particles. Defects or cracks in the seed layer could lead to defects in the grown membrane.115,125,126 Also, the selectivity of the membrane cannot be

145 recovered with the cover layer if the defect concentration is too high. 24,124 Thin seed layers would not only lead to a relatively thin grown membrane and minimize the transport resistance but also help better follow and cover the contours of a rough substrate127, thereby reducing the possibility of flex-cracks. In addition, thinner the layer, smaller are the drying cracks.128 However, the probability of producing defects due to incomplete coverage is higher during the deposition of a thinner layer. This effect is especially enhanced for rough substrates like the polymer supports to be used in the proposed work.

Rubbing, electrostatic deposition, electrophoretic deposition, spin-coating and dip-coating are the techniques used by different researchers to obtain a uniform seed layer.115,128,129. Boudreau et al. modified a silicon wafer and used electrostatic attraction to adsorb zeolite A particles (~300 nm in size).129 They obtained complete coverage with just one coating but the particles were not close-packed. In this process, substrates have to be modified chemically using sequential coatings with charged polymers to have opposite charge to that of zeolite particles. Not only are such processes more complicated to scale up, but they also require post-process removal of the polymer. Dip-coating is the most favorable technique from the point of view of scale-up. In this process, the substrate to be coated is dipped into the coating solution vertically or at an angle and then withdrawn at a given speed. The film thickness is controlled by a balance of viscous drag with either the gravity or the surface tension forces. On solid substrates like silicon wafers, glass and non-porous alumina, dip-coating of zeolite suspensions (in the absence of any polymers) has yielded only limited success in terms of achieving complete surface

146 coverage. For example, Boudreau et al. used multiple coatings and slow withdrawal speed to improve the coverage of zeolite particles. This was largely due to the inherent poor film-forming ability of particles as compared to polymers and also the low viscosity of dilute colloids.

However, on porous substrates, dip-coating is always accompanied by not only simple film coating but also slip casting where the liquid in the coating sol is absorbed by the pores. This liquid draining helps in speedy consolidation of particles on the substrate, thereby forming a close-packed particulate layer. Coherent zeolite seed layers have been obtained on porous inorganic supports.114,115,125 The slip-casting effect could dominate for a low viscosity coating dispersion especially in the absence of any film-forming polymer.

The rate of deposition in slip casting is given by the following expression:130,131,132

K dP Q r (5.1) dz where „Pr‟ is the pressure, „Q‟ is the deposition rate or the liquid flux, „K‟ is the permeability of the porous media, „µ‟ is the viscosity of the coating dispersion and „z‟ is the position variable in the flow direction. In the absence of any external force, Pr is same as the capillary suction pressure:

4 Ps (5.2) d p considering the substrate pores as horizontal capillaries.132 In Equation 5.2, „ ‟ is the interfacial tension between the liquid and the substrate material, a measure of its hydrophilicity or lyophilicity and „dp’ is the diameter of the pores in the substrate. It is

2 important to note that although Ps α 1/ dp, K α dp (by Hagen-Poiseuille equation) due to 147 which the deposition rate decreases as the pore diameter reduces. Also, the pressure „Ps’ would reduce to zero when the substrate pores get saturated with the liquid. The ceramic supports, for example porous alumina used by White et al.114 and Kuzniatsova133, are generally thick (~2 mm) with a porosity of about 30 – 40% due to which they have a substantial unsaturated pore volume during coating. This can keep the suction pressure high and give sufficiently high deposition rates. White et al. used such alumina supports with a pore size of about 40 nm to obtain a good surface coverage of close-packed zeolite

Y particles. Figure 5.2 shows the top surface of their zeolite seed layer.

Polymer supports, on the other hand, are different in morphology to the ceramic supports. They are generally produced as a two-layer composite structure with the polymer of interest supported on a porous fabric. The total thickness is about 100 – 300

µm and the total bulk pore volume is small due to the small thickness. This could reduce the slip casting effect by pore saturation during the coating process.

A similar issue was tackled by Pan et al. for coating thin-walled ceramic hollow fibers with alumina particles.134 They used evacuation to increase the suction and form a continuous layer in a cross-flow filtration set-up. Huang et al. obtained a uniform layer of zeolite A seed particles (500 – 1500 nm) on alumina supports using vacuum-assisted dip coating.135

The role of the colloidal dispersion is important in this regard in addition to the deposition process. The more stable the dispersion is, lesser is the number of aggregates and consequently, a more close-packed and dense particulate layer could be formed. This means there is minimal subsequent particle rearrangement and shrinkage due to which

148 less cracking occurs.128,132,133 Ultrasonication is the usual method for dispersing the zeolite particles in water. White et al. made their seed layers using ultrasonicated zeolite

Y dispersions in water (pH~8.5). Kuzniatsova et al. showed the effect of pH on the zeolite Y dispersion stability, and consequently on the surface coverage and layer quality.

They obtained the most uniform zeolite Y seed layer at an optimum pH of 11.5.

5.4 Experimental

5.4.1 Materials

The NL nanoporous polysulfone support (thickness of 160 µm including a non- woven fabric support) was kindly provided by NL Chemical Technology, Inc. (Mount

Prospect, IL). Biomax PES ultrafiltration membranes (thickness of 270 – 330 µm including a non-woven fabric support) of different molecular weight cut offs; 30 kDa, 50 kDa, 100 kDa, 300 kDa and 1000 kDa (kDa: kilodaltons) were kindly provided by EMD

Millipore (Billerica, MA). Sterlitech PES (free-standing) microfiltration support with a nominal pore size of 30 nm and thickness of 50 µm was purchased from Sterlitech

Corporation (Kent, WA). All these supports were also characterized by scanning electron microscopy to obtain a more accurate picture of their surface morphology.

Polydimethylsiloxane (PDMS) was kindly provided by Wacker Silicones, Inc. (München,

Germany) as a viscous liquid product with a trade name Dehesive® 944. The corresponding crosslinker (Wacker® Crosslinker V 24) and catalyst (Wacker® Catalyst

OL) were also provided. Zeolite Y particles of roughly two sizes, 200 nm and 40 nm were obtained from the Dutta group in the Department of Chemistry. The procedure used

149 to prepare and characterize these particles is given by White et al. and Kuzniatsova et al.114,133 The sizes mentioned are close to the averages obtained by Dynamic Light

Scattering.

5.4.2 Lab-scale coating

Some of the initial experiments on polymer supports were performed using dip- coating. In this case, the coating solution was spread evenly on the substrate attached to a glass plate in a horizontal position after which it was allowed to stand in a vertical position thereby draining all the solution. Later, in order to avoid saturating the relatively thin polymer supports during dip-coating, a vacuum dip-coating apparatus was set up.

There is a circular holder (Figure 5.3) with one end connected to a Duoseal 1405 liquid ring vacuum pump. The support to be coated is taped onto a fixed flat porous metal plate supported on the holder. The top surface of the support is then dipped tangentially (as in crossflow filtration) into the coating dispersion for a couple of seconds and then taken out. The vacuum in addition to assisting the layer formation helps to keep the support flat during the coating process. A bypass was used to control the downstream vacuum, if needed. When the bypass was completely closed, the downstream pressure went down to about 3 inches Hg. All the results discussed in Section 5.5 were obtained using these conditions. Millipore PES supports are sold with glycerol in the pores which is removed using water washing followed by dipping in isopropanol (IPA). Each dipping step was done for at least 30 minutes.

In the last step during fabrication and also for transport characterization, the membrane was spin-coated with a polydimethylsiloxane (PDMS) solution using WS-650

150 spin-coater from Laurell Technologies. The PDMS, obtained from Wacker Silicones,

Dehesive® 944 is a 30 – 40% solution in an organic solvent. The PDMS solution for the coating was prepared by dissolving 2.5 g of Dehesive® 944 in 16.2 g of heptane. The corresponding crosslinker and catalyst were then added in the ratio 100:1:0.5 (PDMS:

Crosslinker: Catalyst). The coating procedure used was as follows: The PDMS solution was spread evenly on the stationary substrate. After the spreading, the spinning speed was increased to 1000 rpm and maintained for 10 sec after which it was increased to 3500 rpm for a minute. The coated membrane was dried in the hood for 30 minutes after which it was cured at 100 °C for 30 minutes. This same procedure was used to PDMS-coat different substrates. For the more viscous PDMS solution preparation, about 3.9 g of

Dehesive® 944 was dissolved in 9.3 g of heptane. The spin-coating speed was increased to 5000 rpm instead of 3500 rpm and the solution was spread on an already rotating substrate at 2000 rpm. In order to eliminate effects due to blocking of intrazeolitic pores by water, one sample was prepared by coating with PDMS solution after drying at about

100 °C under vacuum.

In order to characterize zeolite (~40 nm particle size) particulate layers as supports for other selective layers, we developed a procedure to minimize/eliminate infiltration of the PDMS solution into the zeolite layer. Water was evenly spread onto the surface followed by spinning at 1000 rpm for 10 sec followed by 5 sec at 3000 rpm. This was repeated five or six times after which the PDMS was coated and cured by the usual procedure. For comparison, we made coatings on bare Millipore PES 300 kDa and NL

PSf supports also. For PDMS coating on the bare PES support, the glycerol in the pores

151 was removed after the PDMS curing by overnight immersion in IPA. The NL support was dipped into glycerol/IPA (2:3 by wt.) solution overnight prior to PDMS coating.

After PDMS coating and curing, the glycerol was removed as before.

5.4.3 Imaging by scanning electron microscopy

For SEM, the PSf supports were immersed in IPA overnight at room temperature before sample preparation. The PES supports were also immersed in IPA to remove the glycerol in their pores. The Sterlitech support was used as received. The samples were gold-coated prior to imaging. The cross-sectional imaging was done using a Focused Ion

Beam (FIB) in combination with SEM. The top surface images were analyzed using the

Clemex Image Analysis software to estimate the surface porosities and mean pore sizes reported in Table 5.1.

5.4.4 Transport characterization

The gas permeation set up shown in Figure 3.8 was used to test the PDMS-coated zeolite particulate layers. Most of the measurements were performed under dry conditions. For wet gas measurements, the feed side humidifier vessel was filled with water upto a volume of 60% of the total volume. The feed gas was then bubbled through it. Due to the uncertainty in the water balance in these experiments, the permeance measurements had a corresponding standard error shown in Figure 5.16. For low selectivity (CO2/N2) and reasonably high to very high permeances reported in this chapter, the counterdiffusion of Ar sweep gas through the membrane can be significant.

This was taken into account for membrane performance evaluation. The net change in total flow on both feed and sweep sides was small due to which log-mean driving force

152 was assumed to represent the driving force for permeance through the membrane and the selectivity was calculated using the ratio of log-mean permeances.

Most of the tests were conducted using the small rectangular cell (area: 2.71 sq.cm) while some were performed using a circular cell of area 5.71 sq.cm. The test temperature was 57 °C and feed and sweep pressures were 1 atm each. 25% CO2 and

75% N2 was used as the feed gas for these tests. High sweep flow of around 300 cc/min was used for these tests to eliminate any sweep side mass transfer resistances at high permeances.

5.5 Results and discussion

Dispersions of different zeolite Y concentrations were prepared in water. They were ultrasonicated at room temperature for around 90 minutes before coating. The water was changed intermittently (every 15 minutes) to prevent too much of a temperature rise.

After the deposition, the seed layers were dried overnight at room temperature prior to further characterization or PDMS coating for transport measurements.

5.5.1 Identification of appropriate polymer supports

The inherent hydrophilicity of the common ceramic support, alumina, is comparable to that of polysulfone and in fact, less than that of polyethersulfone which are the two most widely used polymeric ultrafiltration and microfiltration membrane materials.136,137 The first dip-coating experiments were performed using the NL PSf support (surface pore size: ~9 nm, surface porosity: ~7%). Although, the pore size and porosity were considerably lower than that of alumina133, we were interested in using this

153

support due to its ease of availability. The surface morphology of the support along with

that of TriSep PSf are shown in Figure 5.4.

The top surface of the seed layer on the NL PSf support is shown in Figure 5.4

(b). It should be noted that vacuum was not used for these experiments. Also, the 200 nm

zeolite Y particles were used at a concentration of about 0.5 wt%. The zeolite particles

did not form a coherent layer. Instead, they formed loose aggregates and settled randomly

on the surface of the support. The small pore size of NL support and the resultant viscous

resistance to the liquid draining through the support are believed to result in an

insufficient slip-casting effect.

We then used the Sterlitech PES support for the same experiment. This support

has a larger pore size and surface porosity than NL PSf support. The top surface of the

100 µm coating is shown in Figure 5.5. It can be seen clearly that the surface coverage was better than on NL support. Also, the particles were more close-packed in this case. This can be

attributed to the greater deposition rate on Sterlitech support due to the larger pore size.

Although the particle packing was better than on NL support, it was not as tightly packed

as in the case of alumina support (Figure 5.2). This could be due to the support pore

saturation. This support thickness is only about 50 μm as opposed to the alumina support

which is about 2 – 3 mm in thickness. In order to obtain a better coating at this point, we

set up the vacuum dip coating apparatus. We identified three commercial PES supports 5 kDa stands for kilo-Dalton on which a favorable coverage of zeolite seeds could be obtained. The top surfaces of all

these supports have been shown in Figure 5.6. The image analysis data is shown in Table

5.1. As indicated by the data, all these supports including Sterlitech support have a larger

154

pore size and surface porosity than the previously used NL support. The slightly greater

hydrophilicity of PES vs. PSf could also help in the deposition.

10 µm 10 µm 5.5.2 Seed layer deposition by vacuum dip-coating For the 200 nm zeolite Y particles, we used the Sterlitech PES and Millipore 1000

kDa PES supports. Figure 5.7 shows an example of the coating on Sterlitech PES

support. The coatings show a color pattern throughout the surface due to an optical

opalescence effect which is typical of thin uniform layers.138 Figure 5.8 shows the images

of top surface and cross-section of the sample obtained by SEM. These colors can also be

seen for a similar coating on Millipore 1000 kDa PES support. Figure 5.9 shows an

optical microscopic image of the same. The dark spots or patches on the background are

macroscopic defects or non-uniformities of the support.

The top view in Figure 5.8 shows a fairly close packing of zeolite Y particles

similar to that seen in Figure 5.2. The cross-sectional view obtained using FIB etching

and SEM shows a thickness of about 1 μm. Figure 5.10 shows a similar coating

performed on the NL support. As it can be seen, the surface coverage was not very good

despite the use of vacuum. This shows that, if the pore size is too small, it is difficult to

obtain enough suction even with vacuum.

We were also interested in coating the polymer supports with smaller zeolite

particles to obtain a relatively smaller interparticulate pore size. This is more favorable

for subsequent growth to fill these pores or even from the point of view of using these

layers as porous substrates or intermediate layers. For this, we have done some initial

experiments on Millipore PES 1000 kDa and Millipore PES 300 kDa supports. Sterlitech

155 support could not reproducibly form a layer with the smaller particles because of its large pore size.

We started with a coating of about 0.58 wt% dispersion of ~40 nm zeolite particles on MP 1000 kDa support. The top surface obtained was full of cracks and is shown in Figure 5.11. We then reduced the concentration of the dispersion to about 0.19 wt%. Also, assuming that drying rate was too high, we started drying the samples under controlled humidity conditions (70% relative humidity at room temperature with stationary air). The optical microscopic images of the resultant coatings on both MP 1000 kDa and MP 300 kDa supports have been shown in Figure 5.12 and Figure 5.13 respectively. It can be clearly seen that the size of cracks has drastically reduced at the lower concentration and consequently, reduced thickness. They can be observed only when viewed carefully. But, the cracks still occurred suggesting that subsequent drying after the deposition was probably not playing a great role. The cracks in such layers usually originate during initial consolidation and drying. It is known that these cracks increase in width with thickness.128 Also, these cracks seem to appear more for the smaller particles due to the larger drying stresses associated with smaller spaces between the particles.

Figure 5.14 shows the coatings with about 0.19 wt% dispersion on these supports as seen using a digital camera. As discussed before, the color patterns show the presence of a continuous zeolite layer from a macroscopic view.138 But they do not explain enough about the quality of the layer as shown by the previously discussed images.

156

We then attempted to make the layer thinner by diluting the dispersion to about

0.1 wt%. Figure 5.15 shows the top-surface SEM image of the seed layer deposited with about 0.1 wt% dispersion on MP 300 kDa. With this concentration, it was not possible to get a coverage of ~40 nm particles on the 1000 kDa support which had a higher number of large pores (>200 nm) than the 300 kDa PES support. On MP 300 kDa support, the dilution resulted in a thinner layer with much fewer cracks having an average width of less than 100 nm or so. A thickness of less than 400 nm or so was confirmed by cross- sectional SEM using FIB. Such a thin seed layer is highly desirable for the high permeance zeolite Y membrane and also for use as a substrate.

We also performed some adhesion check experiments for these particles using a scotch tape test. In this test, the scotch tape is flattened evenly on the top surface and then ripped off. From the force used to remove the tape and the residue left on the tape, conclusions can be drawn about the quality of the adhesion between the top surface and the layer beneath. The results can be classified qualitatively. For the 40 nm particles on

MP 300 kDa support, the adhesion was good. But for the 200 nm particles, the adhesion was poor. This can be explained by the fact that the smaller particles due to their size can come into a much more intimate contact with each other as well as the substrate layer. So even from an adhesion point of view, smaller particles are preferred.

5.5.3 Transport measurements

The seed layer formed by zeolite particles has interparticulate pores. For zeolite particles of ~40 nm size, the interparticulate pore size is <10 nm (see Chapter 6.2). In order to obtain a selective zeolite membrane, the interparticulate pores need to be closed

157 or plugged via growth. Although, obtaining a purely zeolite-based selective layer was out of the scope of this dissertation work, we covered the seed layer with PDMS to plug these pores and characterize the layers through transport measurements. PDMS infiltration into the gaps between the particles can drastically reduce the effect of interparticulate pores on the transport. Figure 5.16 shows these results. The selectivity of all the PDMS-coated zeolite membranes was only between 8 to 10. Although low, it was significantly higher than that of PDMS which gave a maximum selectivity of about 5.5 at 57 °C. This can be explained by the mixed-matrix effect at the interface between PDMS and zeolite Y

139 particles where CO2 can get preferentially sorbed. The drastic reduction in permeance on the other hand, shows that a continuous seed layer was formed. It also indicated that the infiltration into the zeolite layer and into the underlying porous substrate was severe.

Although growing a polycrystalline layer was out of the scope of this work, Figure 5.16 shows one data point corresponding to a preliminary growth experiment. The result was similar to the other experiments with the seed layers. But, in this case, the PDMS coating was done twice due to the rough nature of the grown zeolite layer.

We also wanted to evaluate the zeolite-coated polymer supports as hybrid substrates. After avoiding infiltration by appropriate pore filling methods, we can see that the zeolite-coated Millipore 300 kDa gave the highest CO2 permeance (between 2700 to

4000 GPU). This was probably due to the high surface porosity of these substrates at a relatively small pore size compared to conventional polymer supports. This idea will be built upon and discussed in greater detail in Chapter 6.

5.6 Conclusions 158

1) The work described in this chapter was aimed towards developing a scalable method

for depositing defect-free zeolite layers on commonly used polymer supports. In this

effort, we set up a vacuum dip-coating apparatus which was conveniently used to

obtain thin (<1 μm) coatings of zeolite particles on these supports.

2) We identified the favorable porous support surface morphologies that can allow a

successful deposition to occur. These properties can then be targeted in a pilot-scale

phase inversion process to fabricate appropriate supports, if needed.

3) We also studied the effects of coating dispersion concentration and particle size on

the dried layer thickness and quality. The relation between layer thickness and crack

formation was also explored. Smaller particles were found to be more prone to

cracking than larger particles at the same thickness. But, the smaller particles were

used advantageously to reduce the layer thickness and the interparticulate pore size.

4) The seed layers can be used to grow polycrystalline zeolite layers or used as high

porosity substrates for polymer membranes. This work could also be adapted to other

separations that use inorganic membranes as selective layers and applications such

ultrafiltration/nanofiltration. It can potentially improve the economics of inorganic

membrane fabrication for a wide range of applications.

Acknowledgements

The authors would like to thank Lang Qin for helping us obtain some of the SEM and

FIB-SEM images and Michael Severance for providing us the zeolite particles. We are grateful to Paul Green at the ChBE machine shop. The authors would also like to thank

159 the Department of Energy/National Energy Technology Laboratory (DE-FE0007632) for the financial support of this work. This work was partly supported by the Department of

Energy under Award Number DE-FE0007632 with substantial involvement of the

National Energy Technology Laboratory, Pittsburgh, PA, USA.

160

Table 5.1. Surface morphology of the different supports used for zeolite deposition studied in this work. These numbers were obtained through analysis of SEM images

shown in Figures 5.4 (a) and 5.6.

Mean pore size; Surface Largest pore size Porosity Support (nm) (%)

Sterlitech PES ~96; 810 ~14.4

Millipore 1000 kDa PES ~57; 683 ~17.1 Millipore 300 kDa PES ~62; 385 ~15.4

NL ~8.8; 35 ~6.9

161

Figure 5.1. Faujasite (FAU) (zeolite X or Y) cage structure.140

162

Figure 5.2. Zeolite Y seed layer top surface in Reference 114. 114

163

Figure 5.3. Schematic of the vacuum-assisted dip-coating set-up.

164

500 nm 20 µm

(a) (b)

500 nm

(c)

Figure 5.4. Zeolite Y dip-coated (0.5 wt% dispersion in water, ~200 nm particles) onto NL PSf support. (a) Bare NL PSf support, (b) With zeolite coating on NL PSf,

and (c) Bare TriSep PSf support.

165

Figure 5.5. Zeolite Y dip-coated (0.5 wt% dispersion in water, ~200 nm particles)

onto Sterlitech PES support.

166

(a)

2 µm

(b)

3 µm

(c)

Figure 5.6. Commercial PES supports used for zeolite Y coating. (a: Millipore 300 kDa PES, b: Millipore 1000 kDa PES, c: Sterlitech PES).

167

Figure 5.7. Zeolite Y vacuum dip-coated (0.5 wt% dispersion in water, ~200 nm

particles) onto Sterlitech PES support. (left, Uncoated; right, coated).

168

Figure 5.8. Zeolite Y vacuum dip-coated (0.5 wt% dispersion in water, ~200 nm

particles) onto Sterlitech PES support.

(left, top view, SEM image; right, cross-section, FIB-SEM image).

169

Figure 5.9. Optical microscopic image of zeolite Y vacuum dip-coated

(0.5 wt% dispersion in water, ~200 nm particles) onto

Millipore PES 1000 kDa support.

170

Figure 5.10. Zeolite Y vacuum dip-coated (0.5 wt% dispersion in water, ~200 nm

particles) on NL PSf support.

171

Figure 5.11. Optical microscopic image of zeolite Y vacuum dip-coated

(0.58 wt% dispersion in water, ~40 nm particles) onto

Millipore PES 1000 kDa support.

172

Figure 5.12. Optical microscopic image of zeolite Y vacuum dip-coated

(0.19 wt% dispersion in water, ~40 nm particles) onto

Millipore PES 1000 kDa support.

173

Figure 5.13. Optical microscopic image of zeolite Y vacuum dip-coated

(0.19 wt% dispersion in water, ~40 nm particles)

onto Millipore PES 300 kDa support.

174

Figure 5.14. Zeolite Y vacuum dip-coated (0.19 wt% dispersion in water, ~40 nm

particles) onto Millipore supports.

(top, on Millipore 1000 kDa; bottom, on Millipore 300 kDa).

175

Figure 5.15. Zeolite Y vacuum dip-coated (0.1 wt% dispersion in water, ~40 nm

particles) onto Millipore 300 kDa support: Top Left: Zeolite layer under lower

magnification, Top Right: Zeolite layer under higher magnification,

Bottom: Cross-section.

176

12 PDMS/ZY-40 (8 hr grown) PDMS/ZY-40 (0.58 wt% dispersion), wet 10 PDMS /ZY-200 nm (vacuum drying) PDMS/ ZY-200 nm (viscous) PDMS/ NL polysulfone, 55 °C PDMS/Millipore 300 kDa, 55 °C 8 PDMS/Millipore 300 kDa, wet PDMS/ZY-40, water filled PDMS/ZY-40, water filled, wet

Selectivity

2 /N

2 4 CO 2

0 0 1000 2000 3000 4000

CO2 Permeance (GPU)

Figure 5.16. Transport characterization of PDMS-coated zeolite seed layers

and PDMS-coated polymer supports.

177

CHAPTER 6

INORGANIC (ZEOLITE)/POLYMER MULTILAYER COMPOSITE

MATERIALS AS SUPPORTS FOR CARBON CAPTURE MEMBRANES

6.1 Summary

PCC is a challenging application for any separation process. As seen in Chapter 4, for a purely membrane-based process, a CO2 permeance of >3000 GPU and a CO2/N2 selectivity of about 150 are required to achieve the economic targets. To achieve these objectives, this chapter reports an attempt using zeolite/polymer-supported amine membranes.

To achieve the afore-mentioned membrane performance, it is important to take a comprehensive look at the entire multilayer structure. Ideal support should have a small pore size with a high surface porosity and low tortuosity. This combination can reduce the infiltration of the coating solution during fabrication and the adverse effects of penetration. High porosities and low tortuosities can also reduce the resistance to gas diffusion through the support. Such a combination of surface properties are more readily achievable in inorganic substrates than polymer supports. But, as seen in Chapter 5, pure inorganic supports are expensive and not scalable. We therefore used the polymer/inorganic (zeolite) composite materials as substrates for this work.

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In Chapter 3, the amine containing polymer membrane was studied and scaled-up with AIBA-K as the mobile carrier and Lupamin® as the fixed carrier. In this chapter, the research on amine-selective layer has been extended to include other types of mobile carriers; TETA and salts of glycine. Lastly, in order to evaluate the stability of the membrane, its tolerance to the presence of SO2, a common minor component of flue gas was also studied. Under no SO2 and under about 0.7 ppm SO2 on wet basis, the membrane showed good stability for the test period of around 30 hours. In the presence of about 5 ppm SO2, the membrane performance dropped to about 30 – 40% of the initial value in close to 24 hours and subsequently recovered to upto about 60 – 85% of the initial value once the flow of SO2 containing gas was stopped.

6.2 Introduction and rationale

High CO2 permeance (>3000 GPU) and reasonably high CO2/N2 selectivity (>

100 and preferably close to 150) are key membrane properties required to achieve the stringent economic targets of PCC using a purely membrane-based capture process. In this context, it is important to take a comprehensive view of the entire membrane structure and eliminate unwanted transport resistances while improving the properties of the selective layer.

6.2.1 Supports

An ideal substrate will offer negligible resistance to transport while providing mechanical stability to an ultra-thin selective layer. It is more necessary to use such a substrate when the permeance through the selective layer is high. In that case, the

179 permeance through the selective layer becomes more comparable to the permeance through the underlying substrate. The series-resistance model (total resistance is the sum of individual resistances) predicts a composite membrane permeance which is lower than both of the above individual permeances.

6.2.1.1 Gas transport through porous materials

Generally, gas transport through porous materials takes place via a combination of

Knudsen diffusion, bulk diffusion, surface diffusion and a pressure-driven viscous flow.

This is shown in Figure 6.1 as a series-parallel model.141 Surface diffusion is generally insignificant in the mesoporous regime (a pore size of 2 – 50 nm) which is characteristic of the ultrafiltration membranes and commonly used supports for gas separation membranes. Common polymer supports are multilayer structures themselves. This means that each layer in the support is a porous material capable of transport depicted in Figure

6.1. The composite structure consists of a top porous polymeric layer prepared by phase inversion and supported on a bottom non-woven porous fabric (Figure 6.2). The top layer is asymmetric when prepared by phase inversion, the technique used in most of such commercial polymer membranes (examples include the TriSep and NL supports used in

Chapters 3 and 5). It consists of a relatively dense skin layer of the required pore size or molecular weight cut-off and a much more porous bulk with also a much larger pore size.

Assuming series-resistance model for the composite structure, generally, the dense skin layer dominates the transport despite being thin at about 100 – 300 nm.24,142

From the model shown in Figure 6.1, it is obvious that viscous flow permeance plays an independent role in the transport. Its presence is always helpful in increasing the

180 total permeance. On the other hand, out of Knudsen and bulk diffusion, the smaller of the two will dominate. For a typical ultrafiltration membrane (such as the NL or TriSep support) with a molecular weight cut off of 50,000 Da (vendor estimate) and pore size of

~10 nm, the surface or skin layer porosity is 5 – 10% with a tortuosity of 2 – 3. Knudsen permeance for any gas through a skin layer 100 nm thick is of the order 105 GPU, which is much higher than targets of PCC. So for pure gas transport through the skin layer, the support will play a negligible role irrespective of whether there is a pressure-driven viscous flow or not.

But, when a mixture of gases is involved (low selectivity and high permeance through the selective layer) or when a sweep gas is involved, the permeant of choice

(CO2 in this case) has to diffuse through the other gas before reaching the bulk of the permeate stream. This continuum diffusion resistance becomes especially important in the absence of a pressure gradient.143,144 This resistance, in addition to depending on each layer‟s thickness, depends strongly on its effective porosity which is defined as εs/τ, where εs is the porosity of the layer and τ is the tortuosity. From the point of view of reducing the continuum diffusion resistance, high surface porosity is therefore preferred in addition to minimizing the thicknesses and tortuosities and maximizing the porosities of all the layers.

6.2.1.2 Effect of infiltration/penetration

The surface or skin layer effective porosity is important also from the point of view of reducing the total resistance in case of infiltration of coating solution into the support. For example, if the infiltration is upto a thickness of 100 nm, the effective

181 thickness increase of the selective layer will be 100/(εs/τ) nm. Low effective porosity will lead to a greater resistance increase in that case.

6.2.1.3 Pore size vs. surface porosity for polymer supports

Common polymer supports are the membranes used in ultrafiltration which include polymers such as cellulose acetate, PSf, PES, polyacrylonitrile etc. As indicated earlier, the skin layer in these membranes usually has a much lower porosity than the bulk. For example, for a series of cellulose microfibers, it was reported that the surface porosity was only about 10% or so for a bulk porosity of about 50%.145 In addition, as the surface pore size reduces, it becomes more difficult to obtain a high surface porosity. For instance, for PES ultrafiltration membranes, the surface porosity was only about 9% for a

10 nm pore while it reduced to 5% or so for a 5 nm pore.142 To obtain a surface porosity

>15% for a PES support, generally the pore size has to be considerably larger than 10 nm.

Although the details will vary with the type of polymer, the general trend is expected to be similar for all the membranes prepared by phase inversion.

This larger pore size requirement has disadvantages when making a thin coating of the selective layer. The coating process can result in more defects and also lead to a greater infiltration of the coating solution into the substrate leading to greater resistance to mass transfer. Ideal substrates have small pore sizes to minimize penetration while having a high surface porosity. Inorganic supports that are usually formed by inorganic particles of different sizes, resemble beds of randomly close-packed particles. In such a bed, the interparticulate pore size depends upon the size of individual particles. By controlling the size of particles, theoretically, the average pore size in the inorganic layer

182 can be controlled. So, better microstructure control is possible. Also, the porosity is independent of the particle size and varies between 30 – 40% for particles of different shapes and a random close-packing configuration.146

But as discussed in Chapter 5, both these kinds of substrates have their advantages and disadvantages. The polymer supports are scalable, cheap and manufactured in relatively small thicknesses. The inorganic supports on the other hand, are relatively expensive and less scalable and barring the new types of metallic porous supports, are usually thick. It will therefore be interesting to combine both these types into a novel scalable multilayer porous material. Zeolite Y (~40 nm particles)/PES 300 kDa was used as the substrate for most of the membranes reported in this chapter.

6.2.2 Amine-based selective layer

The selective layer should have the inherent properties which can potentially meet the economics. Amine-based facilitated transport is attractive due to its potential to combine high selectivities with reasonably high CO2 permeances. Specific to this application, low CO2 partial pressures mean lesser carrier saturation which makes facilitated transport even more favorable. In this context, both fixed and mobile carrier membranes have been studied. El-Azzami et al. measured a CO2 permeability of 320

Barrers with a CO2/N2 selectivity of 120 for a water-swollen chitosan (poly-

(D)glucosamine) membrane.147 Blends of pure PVA with PEI or PVAm have been used

148,149 to obtained CO2/N2 selectivities greater than 150 at room temperature. Deng et al. showed that a permeance greater than 300 GPU with a selectivity close to 150 is achievable for a water-swollen fixed site carrier (FSC) PVAm/ PVA membrane with a

183 selective layer thickness of 0.3 – 0.7 µm.149 In a more recent study,74 Kim et al. synthesized a membrane with almost pure high molecular weight PVAm (molecular weight >340000). The membrane was shown to have extraordinary separation properties with best CO2 permeances and selectivities greater than 1000 GPU and 200, respectively at 35 °C. The exceptional performance of this membrane warrants further research into this easily available commercial material. Various researchers have also used polyamidoamine (PAMAM) dendrimers as carriers. Kai et al. used PAMAM dendrimer- impregnated chitosan intermediate layer on porous polysulfone to fabricate hollow fiber

150 modules. CO2/N2 selectivity of up to 170 was reported but the CO2 permeance was less than 30 GPU at 25 °C. Blends of the dendrimer with Pebax® or quaternary ammonium compounds with Pebax® have resulted in simultaneous increases in both permeability and selectivity.151,152 Such blends are interesting from the point of view of alleviating the unfavorable selectivity-permeability trade-off in solution-diffusion membranes.

Small amine molecules used as mobile carriers can significantly increase the CO2 transport rates. Huang et al. obtained an extremely high permeability of greater than

6000 Barrers and a CO2/N2 selectivity of about 500 at 110 °C using PAA as the fixed carrier and AIBA-K as the mobile carrier in a crosslinked PVA matrix.73 Recently, Yuan et al. showed that the performance of a PVAm membrane can be enhanced to a permeance of 600 GPU with a selectivity of 106 by using ethylene diamine as the mobile carrier.153

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These membranes based on reactive carriers are generally believed to be susceptible to poisoning by impurities and therefore require sulfur polishing before CO2 removal. But recent experimental trials have indicated that this might not absolutely be true. During field test at 35 °C, a scaled up PVAm membrane showed long-term stability

154 (~4 months) with exposure to SO2 and NOx. Good stability in the presence of SO2 has also been reported by Yuan et al. for a membrane with ethylene diamine dispersed in

PVAm.153 In a separate study, a PVAm-based membrane showed stable operation in a

500-hour test under simulated flue gas operating conditions with 200 ppm SO2 and 200

155 ppm NO2.

This chapter demonstrates the use of zeolite/polymer multilayer composite materials, specifically ~40 nm zeolite Y particles deposited on relatively large pore polyethersulfone membranes (shown and developed in Chapter 5) as supports for amine- based membranes. Assuming a hexagonal close-packing of equal spherical particles, an interparticulate pore size of about 9 nm along with a porosity of 26% is expected. For random close-packing of spherical or non-spherical particles, a porosity of 30 – 40% is expected as mentioned earlier.146 This porosity is more than three times the surface porosities attained by polymer supports (5 – 10% for supports such as NL PSf or TriSep

PSf used in this work) prepared by phase inversion for comparable pore sizes. The amine-based layer is similar to that studied in Chapter 3. New carriers like TETA and salts of glycine have been incorporated to increase the separation performance of the membrane. Some membranes were also made on the conventional polymer supports

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(TriSep polysulfone). Some of the membranes were exposed to gas with SO2 to study the effect on membrane performance.

6.3 Experimental

6.3.1 Materials

Poly(vinyl alcohol), S-2217 (92+ wt%) with an average molecular weight (MW) of 150,000 g/mol and a hydrolysis degree of 87 – 89% was supplied by Kuraray America,

Inc. (Houston, TX). It is an experimental grade mostly used for lab-scale experiments. It is a copolymer of vinyl alcohol and 2-(acrylamido)-2-methyl propane sulfonic acid sodium salt.70 Lupamin® was kindly provided by BASF AG, (Germany). The product contained more than 60% by weight of formate salts. 2-Aminoisobutyric acid (AIBA) was obtained from Alfa-Aesar (Ward Hill, MA) and was 99% pure. Glycine, glutaraldehyde (50 wt% aqueous solution), and potassium hydroxide were purchased from Sigma-Aldrich. Triethylenetetramine (TETA) (>60%) which was bought from

Fisher Scientific had about 40% of cyclic and branched triethylenetetramines while linear

TETA made up about 60%. All the above chemicals were used without further purification. Only AIBA and glycine were neutralized with KOH before further use in the membrane preparation. TriSep microporous polysulfone supports (U-100, thickness of

140 µm including a non-woven fabric support) were purchased from TriSep Corporation

(Goleta, CA). The zeolite ~40 nm particulate layers coated on Millipore PES 300 kDa

(ZY-40) and studied in Chapter 5 were used as supports in this chapter.

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Two specialty feed gas mixtures with certified compositions were purchased from

Praxair, Inc. (Danbury, CT) for the gas permeation tests: one consisting of 20% CO2,

40% H2, and 40% N2, and the other consisting of 25% CO2 and 75% N2 (all on dry basis).

Prepurified argon used as sweep gas and as carrier and reference gas for gas chromatography was also purchased from Praxair, Inc.

6.3.2 Membrane preparation

The casting solution for the amine containing layer was prepared by a similar procedure to that outlined in Chapter 3. In the first step, polyvinylalcohol was crosslinked with glutaraldehyde with KOH as the catalyst. The resultant homogeneous aqueous crosslinked PVA solution was then blended with the fixed carrier polymer and the mobile carrier molecules to prepare a very viscous casting solution. For this purpose the solution was mixed under N2 purge for about 60 to 120 minutes depending upon the initial concentration. During this time, both solvent evaporation and room temperature gelling reaction contributed to increase in viscosity of the casting solution. After mixing, this solution was then coated on the substrate flattened on a glass plate using the GARDCO stainless steel film applicator. The gap setting (the distance between the knife edge and the substrate) was adjusted to obtain a given dried selective layer thickness.

We used lupamin® as the fixed carrier polymer and one or two of the three molecules given below as the mobile carriers.

1. Potassium hydroxide (KOH) (in addition to being the catalyst for crosslinking)

2. AIBA-K

3. Triethylenetetramine (TETA)

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4. Lithium glycinate and potassium glycinate

For the preparation of lithium glycinate (Glycine-Li) solution, glycine was initially dissolved in water at around 70 °C. A stoichiometric amount of lithium hydroxide was then added to the glycine solution under stirring and in multiple batches.

The stirring was continued for about 30 minutes after which it was cooled and used.

Potassium glycinate (Glycine-K) solution was prepared using the procedure described previously for AIBA-K solution.

6.3.3 Transport characterization

The gas permeation set up shown in Figure 3.8 was used to test the amine-coated zeolite/polymer membranes. The rectangular cell with membrane area of 2.71 cm2 was used. Log-mean driving force was used to calculate the CO2 permeance. The CO2/N2 selectivity was calculated using the concentration ratios on feed and sweep outlets

([YCO2/YN2]outlet/[XCO2/XN2]outlet). This selectivity, also called the „actual selectivity‟ or

„process selctivity‟ was close to the one obtained using the ratio of permeances under the test conditions for the small rectangular cell. Unless mentioned differently, all the transport characterization was carried out at 102 °C at close to atmospheric pressure. The relative humidities on the feed and sweep sides were adjusted close to 81% and 57% respectively. For all the tests, we aimed to use 20% CO2 on dry basis at the feed inlet. In case of the CO2-N2 mixture (25% CO2), we used N2 as a diluent to reach this concentration. In that case, the CO2 concentration was close to 18%. Feed and sweep gas flow rates were close to 60 and 30 cc/min respectively, on dry basis. For the SO2 tolerance tests, the above gases were mixed with appropriate flows of SO2 containing gas

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(about 300 ppm) using mass flow controllers. Two SO2 levels were obtained at the feed gas inlet of the permeation cell on wet-basis; 0.7 ppm and 5.1 ppm.

For the permeance and selectivity measurements reported in Tables 6.1 and 6.6, standard errors have been reported. These errors are due to the small fluctuations in the

GC peak areas for different times at steady state. The standard error in CO2 permeance is generally less than 1%. The error in selectivity measurement is larger due to the larger uncertainty in measuring the N2 peak area. Under the above test conditions for the rectangular cell, the N2 peak area is very small and close to the level of noise associated with the TCD detector.

6.4 Results and discussion

In earlier research by our group and also for the amine membrane scaled up in

Chapter 3, we used AIBA-K as the mobile carrier and Lupamin® as the fixed carrier.

KOH used as a catalyst for crosslinking is also believed to contribute to CO2 transport.23,73 In an effort to improve the performance of thin amine membranes, we prepared and tested a series of membranes to explore the effects of different constituents/compositions on the separation performance. To identify the contributions, membranes were synthesized with only one or two types of carriers. Membranes were also made on two different types of substrates; TriSep polysulfone and zeolite/polymer composite material (ZY-40). All membranes contained about 20% crosslinked PVA with

60 mol% crosslink degree achieved using glutaraldehyde.

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6.4.1 Membrane thickness estimation

The zeolite/polymer (ZY-40) substrate was thick mainly due to the thickness of

PES substrate bought from EMD Millipore (>300 μm). The selective layer thickness was only a few microns. Also, the cast membranes were small due to limited availability of the support. Due to all these reasons, an accurate thickness measurement could not be made. To tackle this issue, a series of similar membranes with different thicknesses were made on the TriSep support. In this case, the size of the membrane and the support thickness were such that a reasonably accurate estimate of thickness was possible. The measured membrane thickness normalized to the casting solution concentration was correlated with the gap setting. The relationship is shown in Figure 6.3 and was used to estimate the selective layer thickness on the zeolite/polymer substrate.

6.4.2 Membranes with AIBA-K and KOH

Membranes #1 and #2 in Table 6.1 have only one mobile carrier along with the fixed carrier. All other membranes in Table 6.1 were prepared using two mobile carriers

KOH and AIBA-K in addition to the fixed carrier. It is important to remember that in the presence of CO2 and water, KOH exists as K2CO3/KHCO3. It will be useful to look at the reactions of CO2 with these salts and amines before we compare membranes of different compositions and different types of amines.10,156,157,158

With unhindered primary and secondary amines (Glycine-K, Glycine-Li, and TETA):

+ CO2 + 2 R-NH2 R-NH3 + R-NH-COO (6.1)

The carbamate ion, R-NH-COO is unstable in case of sterically hindered amines. So, the reaction goes as:

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+ CO2 + R-NH2 + H2O R-NH3 + HCO3 (6.2)

Finally, carbonate ion can also interact with CO2 and water to form a bicarbonate ion.

2- CO2 + CO3 + H2O 2 HCO3 (6.3)

Comparing membranes #1 and #2, one can see that AIBA-K is more efficient than

KOH on a weight basis. The inherent rate of reaction with amine is much larger than the rate of reaction with the carbonate ions (Equation 6.1 vs. Equation 6.3).158 Thus, despite the fact that bicarbonate ions are smaller than the corresponding carbamate ions of

AIBA-K, we see that the amine is much more effective under the test conditions. It is interesting that this observation is in contrast to what was observed by Zou et al. who concluded that KOH was more effective on the weight basis.69 This difference can possibly be explained by the difference in thickness. The membrane synthesized by Zou et al. was much thicker (>50 μm) where the diffusional resistances should have been much more important than in thin membranes. Correspondingly, the smaller size of

- HCO3 should be more important than for thin membranes.

Membranes #4 and #5 were prepared with both AIBA-K and KOH. When the

AIBA-K amount is gradually increased, the separation performance improves as expected. Let us take a closer look at membranes #2, #4 and #5. For 25% AIBA-K, a

CO2 permeance of about 478 GPU was obtained. Membrane 4 with 25% KOH and 10%

AIBA-K but a reduced amount of Lupamin® (from about 56% in membrane #2 to about

42% in membrane #4) showed a CO2 permeance of about 537 GPU. Assuming a linear increase in performance with increase in AIBA-K content in membrane #5 from membrane #4, we should obtain a CO2 permeance of 661 GPU for membrane #5 (6.5

191 wt% of AIBA-K will add approximately 124 GPU to 537 GPU). This is close to the actual permeance measured for membrane #5 which has 17.1% AIBA-K. The small difference can be explained by the synergy between carbonate/bicarbonate salts and the amines as discussed later in this section. Nevertheless, this analysis shows that the amount of mobile carrier has a direct effect on the performance of these membranes under the test conditions.

But, if we apply the same type of empirical analysis to membranes #1, #2 and #4 or #1, #2 and #5, we cannot obtain 537 GPU and 681 GPU. Instead we reach about 486

GPU and 610 GPU. This difference suggests a synergistic effect due to the simultaneous presence of AIBA-K and KOH. It can be explained by the amine promotion of absorption

158 of CO2 by K2CO3/KHCO3 and has been well-known in the absorption literature.

Amine can act as a catalyst to realize the high absorption potential of potassium carbonate solutions.

The above discussion also shows indirectly that the fixed carrier lupamin® does not contribute too much to the CO2 permeance under these conditions. This point is further discussed via a specific example in Table 6.5. It is interesting to note that this lupamin® has a large proportion of salts (>60%) in addition to polyvinylamine. The preceding discussion suggests that these salts do not cause any appreciable facilitation of

CO2 under the test conditions.

Membranes #3 and #4 were synthesized by different drying conditions. The insignificant difference between their performances shows the drying was pretty

192 equivalent for practical purposes. Therefore, 10 min convective air drying was used in all the membranes shown in Table 6.1.

6.4.3 Membranes with TETA and KOH

Since mobile carrier seems crucial to the performance of this membrane, we explored new mobile carriers for the same. We first looked into triethylenetetramine, a small non-ionic molecule with a high molar density of unhindered amino groups in its structure, two primary and two secondary amino groups per molecule. It has a comparable molecular weight as AIBA-K (146.2 vs. 141.2 respectively). The loading of

CO2 per molecule is about twice that of AIBA-K for the same weight. This is because two unhindered amino groups are required to absorb one CO2 molecule whereas a sterically hindered amine group has a thermodynamic loading of close to 1 CO2 molecule/amine group (from Equations 6.1 and 6.3). At the same time, it has a lower rate constant than the unhindered amine. All in all, TETA is expected to react faster and absorb more CO2 compared to AIBA-K based on its structure. But, one downside is that

TETA is non-ionic and has a boiling point of 280 °C. Although this temperature is much higher than the test temperature of 102 °C, it does have a finite vapor pressure. In the presence of a sweep gas providing driving force for mass transfer, TETA was found to evaporate as evidenced by the unstable and reducing transport performance after reaching a maxima. Thinner membranes were more unstable. Nevertheless, the initial stable result was used to derive conclusions about how the favorable structure of TETA can help in augmenting CO2 transport.

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Comparing membranes #5 and #6 in Table 6.1, we find that TETA is more effective than AIBA-K in combination with 25% KOH on a weight basis. Under CO2 absorption, the corresponding carbamate with TETA should be bulkier than AIBA-K.

Even then, a higher performance is obtained which shows that the larger number of amino groups and greater inherent reaction rate of unhindered amine vs. sterically hindered amine makes TETA to be more effective under these conditions.

On zeolite particles (membrane #7), the performance was even higher. This could apparently be due to the fact that ZY provides a more porous surface less susceptible to the effects of limited penetration. However, more comparative experiments are required to establish the effect of substrate. This is discussed again later for Table 6.6 where the water transport through these membranes has also been discussed (Section 6.4.5).

Table 6.2 shows more membranes with a similar composition as membrane #7 in

Table 6.1. The difference is that they are considerably thicker and have been cured for a longer time. Comparing membranes #2 and #3 in this table, one can see that the longer curing time than about 3 hours does not cause a significant difference in the initial membrane performance.

Comparing membranes #1 and #2, one can see that the difference can be explained by the difference in the composition. With a reduction of about 45% in the

TETA amount (from 20% to about 11%), a greater reduction in membrane performance was expected assuming a linear reduction. But, the CO2 permeance of about 920 GPU for membranes #2 and #3 suggests that the contribution of amine-promoted CO2 absorption by KOH must be significant in these compositions.

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The instability of TETA membranes caused by the small volatility of TETA was discussed briefly. The fact that the thin membrane in Table 6.1 gave a similar performance as the thick membranes in Table 6.2 also reinforces this point. The time required to escape the matrix from a thinner membrane should be shorter due to the shorter diffusion path distance.

6.4.4 Membranes with lithium and potassium salts of glycine and KOH

Prior to the efforts with AIBA-K as the mobile carrier in a base-crosslinked PVA matrix, Ho studied various salts of amino acids as carriers in the hydrophilic blend of

PVA and polyamines.62 Salts of glycine were found to be significantly more effective than salts of AIBA. In this study, we used glycine-Li in the crosslinked PVA matrix along with polyamines.

Table 6.3 shows four membranes prepared with lithium salt of glycine replacing

TETA or AIBA-K as the mobile carrier. As seen in this Table, the CO2 permeance increased to more than 1000 GPU for 4 – 5 μm membranes. The performance was comparable to a thick TETA membrane (Table 6.2) and much better than a very thin membrane with AIBA-K prepared on the TriSep support (Table 6.1). More direct comparison with AIBA-K at a similar thickness and with the same support is discussed later. Three membranes (#2 to #4) were used to study the membrane stability under different SO2 levels as discussed later. Comparing membranes #1 and #2, we find that by replacing KOH with glycine-Li, the performance does not change much. But, we have also seen before that KOH alone is not as efficient as the amines. So, this again suggests a significant synergy between KOH and amines. This composition change was also

195 motivated by the fact that at high KOH levels in the membrane along with glycine Li, the formation of LiOH and consequently the water- insoluble Li2CO3 is more likely.

Figures 6.4 to 6.6 show membrane performance with time for lithium glycinate containing membranes. Figure 6.4 shows the membrane stability in the absence of SO2.

The membrane showed good initial stability at a CO2 permeance of >1000 GPU and a

CO2/N2 selectivity of >500. Figure 6.5 shows a comparable performance of a similar membrane in the presence of about 0.7 ppm SO2. Figure 6.6 shows the membrane performance in the presence of about 5 ppm SO2. With this higher concentration of SO2 on the wet basis, the performance drops significantly to about 300 – 400 GPU in around

24 hours. A stable performance was observed at room temperature for PVAm-based

153,154,155 membranes even under higher levels of SO2. The disagreement between literature and this work presumably shows the effect of kinetics of the reaction between

SO2 and amine on the membrane performance. After SO2 exposure for around 24 hours, its flow was stopped which initiated a process of membrane performance recovery. About

80 – 85% of the membrane performance was recovered. This showed that the performance drop in the presence of SO2 may not all be due to the irreversible consumption of amines by SO2.

Further investigation is required to explore the fundamental reasons behind this phenomenon. That should enable the exploration of remedial options such as incorporation of certain additives or catalysts that can slow down or prevent the drop in membrane performance. We studied potassium sulfite as a potential additive based on

159 previous literature. But the membrane with 5% K2SO3 showed a similar trend with SO2

196 treatment. The recovery in this test (Figure 6.7) was in fact lower at about 60 – 65%. It will be difficult to say that this was due to K2SO3 since K2SO3 is expected to reduce the effect of SO2 by providing some reversibility for the SO2-amine poisoning reactions and also itself act as a SO2-carrier. The lower recovery is possibly due to some other unknown variation. For now, it can be inferred that the performance recovery is between

60 – 85% after the flow of SO2 containing gas is stopped.

Table 6.4 summarizes the results obtained with glycine-K instead of glycine-Li.

The preparation of glycine-K does not require heating of glycine solution due to the higher solubility of KOH vs. LiOH. Due to this fact, the synthesis is more reproducible as the possibility of oxidation is avoided. Tee et al. found out for salt of dimethyl glycine that replacing Na+ with Li+ as the counterion resulted in a better performance.68 This was mainly due to its smaller size which can affect both the diffusion coefficients and also the amount of amine in the membrane for the same wt% of salt. But, Table 6.4 shows that with the same amount of glycine-K, the performance is not significantly different from the membranes with glycine-Li. This could be due to the possible oxidation of Glycine-Li solution during synthesis.

When the amount of glycine-K is increased, the performance varies fairly proportionally (membranes #2 and #3). But, when the thickness is reduced, although the permeance increases, the change is not proportional (membranes #2 and #4).

Table 6.5 shows different compositions prepared by replacing glycine-K with either AIBA-K or the fixed carrier lupamin®. With AIBA-K, the performance is much lower for a membrane of comparable thickness. It is only about half of the performance

197 with glycine-K. This can be rationalized by looking at the molecules more carefully.

Glycine-K has a molecular weight of 98.1 whereas that of AIBA-K is 141.2. In addition, it is a linear molecule whereas AIBA-K is branched (Figure 3.2). So, the diffusion coefficient should be significantly higher. Also, on a weight basis, there will be more molecules. Although, based on the steric hindrance effect, AIBA-K is expected to have a greater absorption capacity on a mole basis.157

When the glycine-K is replaced by more of lupamin®, the performance reduces even more drastically (comparing membranes #1 and #3 in Table 6.5). This shows perhaps a similar effect wherein the fixed carrier is not effective since the hopping mechanism is presumably much slower than the direct diffusion of small molecules under these conditions.

6.4.5 Effect of substrate

Table 6.6 shows the comparison between membranes made on ZY-40 nm particles and TriSep support. The difference between the CO2 permeances seems higher at larger permeances. If the water permeances are compared, this effect is even more pronounced since water has a very high permeability through this hydrophilic membrane.

At very high permeances, the resistances due to a small amount of infiltration and/or continuum diffusion are likely to be more important.160 More experiments and modeling the transport through the multilayer membrane will be required to verify and understand these effects more quantitatively.

6.5 Conclusions

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1) Zeolite particulate layers of ~40 nm zeolite particles deposited on ~60 nm

polyethersulfone ultrafiltration membranes were successfully used as substrates for

high performance amine membranes.

2) Selective layers of different compositions were synthesized to study the effect of

different components on the membrane performance.

3) Thin membranes with AIBA-K and KOH as the mobile carriers and lupamin® as the

fixed carrier gave a maximum CO2 permeance of close to 700 GPU and AIBA-K was

found to be much more effective than KOH on a weight basis.

4) Both TETA and glycine-based lithium and potassium salts gave a superior CO2

permeance relative to AIBA-K. Membranes with TETA were not stable but the high

amine density in TETA proved to be beneficial for CO2 transport.

5) Glycine-Li- and glycine-K containing membranes also gave a significantly better

performance than membranes with AIBA-K. This was most probably due to the

smaller size of glycine vs. AIBA and the resultant higher diffusion coefficients and

higher carrier amount in the membrane on a weight basis. Membranes with Glycine-

K reached a permeance >1200 GPU at an appropriate thickness and/or carrier

concentration.

6) Membranes with glycine-Li as the major carrier were studied for their initial stability

in the presence and absence of SO2. The membrane was demonstrated to be stable for

close to 30 hrs without SO2 and with 0.7 ppm SO2 on wet basis. Under 5 ppm SO2 on

wet basis, the performance showed an initial drop which recovered to upto 60 – 85%

of the initial value after the SO2 flow was stopped.

199

Acknowledgements

The authors would like to thank the Department of Energy/National Energy Technology

Laboratory (DE-FE0007632) for the financial support of this work. This work was partly supported by the Department of Energy under Award Number DE-FE0007632 with substantial involvement of the National Energy Technology Laboratory, Pittsburgh, PA,

USA.

200

Table 6.1. Membranes with AIBA-K/TETA/KOH as the mobile carrier. All were dried by the same method: 10 minutes of convective air drying at 120 °C. Only membrane 3

dried at 120 °C for one hr without forced convection. Expected thickness for these

membranes is <1 μm. Notation: „P‟: Crosslinked PVA, „K‟: KOH, „A‟: AIBA-K, „T‟

TETA, „L‟: Lupamin®, „Gly-L‟: Lithium glycinate, „Gly-K‟: Potassium glycinate, and

„KS‟: Potassium sulfite.

Composition Substrate PCO2 αCO2/N2 αCO2/H2

1 20.5% P, 25.1% K, 54.4% L TriSep 284±2.4 86±5.7 12.1±0.3

2 19.1% P, 25.1% A, 55.9% L TriSep 478±0.4 108±0.1 11.2±0.1

3 21.5% P, 26.3% K, TriSep 528±3.0 164±12 40.2±0.3

10.6% A, 41.5% L

4 21.5% P, 26.3% K, TriSep 537±1.9 160±13 45.7±0.5

10.6% A, 41.5% L

5 20.1% P, 24.7% K, TriSep 681±6.4 208±15 43.8±0.9

17.1% A, 38.1% L

6 21.3% P, 24.8% K, TriSep 819±5.9 251±21 53.1±0.8

17.1% T, 36.8% L

7 21.1% P, 24.8% K, ZY-40 1026±6.8 208±13 50.0±0.6

16.7% T, 37.4% L

201

Table 6.2. Membranes with TETA/KOH as the mobile carriers.

All were prepared on the ZY-40 substrate.

Composition Expected Curing PCO2 αCO2/N2 αCO2/H2

thickness time (GPU)

(μm) (hrs)

1 19.9% P, 24.2% K, ~7.4 3 1065±4.5 1617±14.5 214±2.1

20.0% T, 35.9% L

2 18.8% P, 32.2% K, ~6.0 3 919±3.3 726±67 275±2.3

11.4% T, 37.6% L

3 18.8% P, 32.2% K, ~6.0 15 925±3.9 813±43 280±2.7

11.4% T, 37.6% L

202

Table 6.3. Membranes with lithium glycinate/KOH as the mobile carriers.

All were prepared on the ZY-40 substrate. *Only this membrane in this table was tested

with a CO2-N2 mixture.

Composition Expected Curing PCO2 αCO2/N2

thickness time (GPU)

(μm) (hrs)

1 19.9% P, 25.8% K, ~ 4.7 90 min 1001±5.6 868±154

19.8% Gly-L, 34.5% L

2 20.1% P, 4.6% K, ~ 4.7 overnight 1102±3.3 960±55

39.9% Gly-L, 35.3% L

3 21.2% P, 4.9% K, ~ 4.7 90 min 1066±2.4 1077±41

39.4% Gly-L, 34.5% L

4* 21.1% P, 5.1% K, ~ 4.7 90 min 1053±5.8 1037±86

39.1% Gly-L, 34.7% L

203

Table 6.4. Membranes with potassium glycinate and KOH as the mobile carriers.

All were tested with a CO2-N2 mixture. All were prepared on the ZY-40 substrate. Curing

time was kept the same at 90 minutes.

Composition Expected PCO2 αCO2/N2

thickness (GPU)

(μm)

1 20.1-21.2% P, 4.6-5.1% K, ~ 4.7 ~1074 ~1025

39.1-39.9% Gly-L, 34.5-35.3% L (average of three membranes)

2 20.3% P, 5.0% K, ~ 4.7 1027±11.8 885±206

40.1% Gly-K, 34.6% L

3 19.4% P, 4.8% K, ~ 4.7 1274±24.3 882±57.3

44.3% Gly-K, 26.7% L, 4.8% KS

4 20.3% P, 5.0% K, ~ 3.2 1168±2.4 802±18.3

40.1% Gly-K, 34.6% L

204

Table 6.5. Comparison between potassium glycinate, AIBA-K and lupamin®. All were tested with a CO2-N2 mixture. All were prepared on the ZY-40 substrate. Curing time

was kept the same at 90 minutes.

Composition Expected PCO2 αCO2/N2

thickness (GPU)

(μm)

1 20.3% P, 5.0% K, ~ 4.7 1027±11.8 885±206

40.1% Gly-K, 34.6% L

2 20.4% P, 5.0% K, ~ 4.8 562±2.1 296±15.8

39.9% A, 34.7% L

3 20.3% P, 4.9% K, ~ 3.8 136±3.7 131±12.2

74.8% L

205

Table 6.6. Comparison between different supports with respect to their CO2 and water

transport. All the results have been already mentioned once in Tables 6.1 to 6.5.

Composition Substrate Expected PCO2 αCO2/N2 PH2O

thickness (GPU) (GPU)

(μm)

1 20.4% P, 5.0% K, ZY-40 ~ 4.8 562±2.1 296±15.8 7639±19.4

39.9% A, 34.7% L

2 20.4% P, 5.0% K, TriSep ~ 4.4 536±0.84 254±3.7 3891±183

39.9% A, 34.7% L

3 21.3% P, 24.8% K, TriSep ~ 1.2 819±5.9 251±21 4090±0.3

17.1% T, 36.8% L

4 21.1% P, 24.8% K, ZY-40 ~ 1.2 1026±6.8 208±13 10580±65

16.7% T, 37.4% L

5 20.3% P, 5.0% K, ZY-40 ~ 4.7 1027±11.8 885±206 8724±696

40.1% Gly-K, 34.6% L

6 20.3% P, 5.0% K, ZY-40 ~ 3.2 1168±2.4 802±18.3 11945±312

40.1% Gly-K, 34.6% L

206

Bulk diffusion Knudsen diffusion

Total flux Surface diffusion

Viscous flow

Figure 6.1. Schematic of the transport mechanism through a porous substrate

(Adapted from Reference 141. 141).

207

Support skin ≈ (0.1-0.3 μm)

Polymer support (~50 μm)

≈ Nonwoven fabric ≈ backing (~120 μm)

Figure 6.2. Schematic of a conventional polymer support.

208

m)/ μ 60

40 y = 20.378x - 1.8911 R² = 0.9146 30

20 Measured Thickness( Measured 10

Casting solution (wt%) solution concentration Casting 0 0 1 2 3 4 5 gap setting (mils)

Figure 6.3. Relation between the gap setting and the measured thickness

normalized to the casting solution concentration.

209

1200 2000

1000 1500 800

600 1000

Selectivity

Permeance

2 2

400 /N 2

CO 500

200 CO

0 0 0 4 8 12 16 20 24 28 32 Time (hrs)

Figure 6.4. Initial membrane stability (no SO2). Membrane #2 in Table 6.3.

210

1200 2000

1000 1500 800

600 1000

Selectivity

Permeance

2 2

400 /N 2

CO 500

200 CO

0 0 0 4 8 12 16 20 24 28 32 Time (hrs)

Figure 6.5. Initial membrane stability (<1 ppm SO2). Membrane #3 in Table 6.3.

211

1200 2000

SO stopped 1000 SO2 introduced 2 1500 800

600 1000

Selectivity

Permeance 2

400 /N 2

CO 500 200 CO

0 0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 Time (hrs)

Figure 6.6. Initial membrane stability and performance recovery (about 5 ppm SO2).

Membrane #4 in Table 6.3.

212

1400 2000

SO2 introduced SO2 stopped 1200 1500 1000

800 1000

600 Selectivity

Permeance

2 /N

400 2

500 CO

200 CO

0 0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 Time (hrs)

Figure 6.7. Initial membrane stability and performance recovery (about 5 ppm SO2).

Membrane #3 in Table 6.4.

213

CHAPTER 7

SUMMARY AND FUTURE WORK

7.1 Summary

7.1.1 Process modeling and cost studies

An important part of this dissertation research was to model membrane reactors and separators and integrate them in overall process schemes for fuel cell H2 purification and post-combustion CO2 capture. A detailed model taking into account mass, energy and momentum balances was developed and the highly non-linear and complex system of partial differential equations was solved using COMSOL Multiphysics which employs the finite element method. The model is one of the most detailed in the published literature for gas separation in spiral-wound membrane modules. Using this tool, the effects of different process variables on the size as well as profiles within the module were studied. Different flow configurations were also compared with respect to size and temperature and concentration profiles.

The above model was simplified and combined with a detailed methodology to calculate capture costs. It was then applied to a purely membrane-based air-sweep process integrated with a coal-fired power plant. The membrane model was solved using

MATLAB and COMSOL Multiphysics while the cost calculations were performed using

Excel spreadsheet. Using this tool, a detailed techno-economic feasibility study was 214 undertaken to establish the effects of membrane and process parameters on final costs.

Membrane performance targets of a CO2 permeance of 3000 GPU and a CO2/N2 selectivity of about 150 were determined which guided the experimental part of the research.

7.1.2 Experimental work on CO2-selective membranes

The experimental work focused on two applications. The first was H2 purification for fuel cells. In that case, the task was to scale up an already well-established lab-scale membrane. For this, larger vessels were set up to carry out the polyvinylalcohol crosslinking and casting solution preparation. Using knowledge of the gelling chemistry and kinetics from the published literature, TETA and EDA were chosen as additives to increase the „gel time‟ of the casting solution. An effective „gel time‟ of about 40 minutes (average) was obtained at high viscosities of the casting solution which enabled to cast about 20 ft of membrane (average) in each run at a web speed of 0.5 ft/min. This enabled the successful fabrication of the first batch of scaled-up amine membrane which was shipped out for spiral-wound membrane fabrication.

For the work on membrane synthesis for PCC, a scalable deposition technique for inorganic particles on polymer supports was successfully developed. This was demonstrated using zeolite particles of two different sizes: ~40 nm and ~200 nm, and a protocol for deposition was established. Also, in this effort, favorable porous support surface morphologies for a successful deposition were identified. The work also looked at the effects of the dispersion concentration and layer thickness on the quality of the coating in terms of cracks and defects. This was studied qualitatively using optical and

215 scanning electron microscopy images. As a proof of concept, the enhancement of separation over the polymer properties was demonstrated using a multilayer zeolite/PDMS structure. Also, using transport characterization, the favorable substrate properties of porous zeolite/polymer composite materials were identified. This property was then successfully exploited in the final part of the work outlined below.

As a final part of this work, multilayer zeolite/amine membranes were studied for

PCC at >100 °C. A high CO2 permeance of >1000 GPU was demonstrated along with a

CO2/N2 selectivity of greater than 500. Also, the effect of different levels of SO2 on the membrane performance was monitored over several hours, and the performance recovery in the absence of SO2 was demonstrated. Different amines were used and compared as mobile carriers. Using results based on water and CO2 permeances, a preliminary comparison between zeolite/polymer and purely polymer substrates of similar pore sizes was made to demonstrate the potential of these novel substrates. Although the performance targets of PCC were not achieved, the membrane showed a good potential to do so in the future.

7.2 Future work

7.2.1 Process modeling and cost studies

The work on process modeling integrated with cost analysis can be extended to other important applications including PrCC and fuel cell H2 purification to shed more light on the economics. The model developed for spiral-wound modules is fairly comprehensive in terms of model equations. There is, however, a lack of experimental

216 data to validate the adiabatic operation of the membrane reactor. Also, prediction of pressure drop which is of practical utility can be validated using lab-scale flow experiments involving flat and thin spacer-filled channels. Basically, more experimental data will be required to improve the model further.

7.2.2 Experimental work on CO2-selective membranes

On the scale-up of the amine membrane, the life of the solution must be further improved to carry out longer runs and fabricate more membrane per batch. For this purpose, composition without fixed carrier could be studied since it was shown that at

>100 °C (Chapter 6), the contribution of the fixed carrier to the overall performance was less than 10% (roughly based on comparison between membranes with and without fixed carrier). Also, fixed carriers that react much more slowly with aldehydic groups at room temperature can also be considered. PEI with a high concentration of tertiary amine groups and non-amine polymers like potassium polyacrylate are possible choices.

Potassium polyacrylate synthesized by neutralizing polyacrylic acid with KOH has a significantly lower tendency to salt out than polyvinylalcohol. Also, very high molecular weight polyacrylic acid is commercially available due to which preparing a viscous casting solution is possible at relatively lower concentrations. Other crosslinkers like diepoxide-based molecules can also be considered due to their lower reaction rates with amines at room temperature. In addition, if it can be verified using chemical and/or thermal analysis that the bulk of EDA is removed during drying, its amount in the final casting solution can be increased further. In addition to modifying the chemistry of the casting solution, mixing and/or processing can also be improved. After centrifuging to

217 remove the air bubbles, the viscous solution can be kept under continuous shear mixing to reduce the rate of gel formation. Also, continuous processing and feeding of the casting solution can be employed to completely eliminate the gelling problem. It is important to have a mixer design that can minimize air entrainment during initial rapid homogenization/blending of crosslinked PVA and polyamines.

Based on the vacuum dipping apparatus used on the lab scale, some other parameters need to be quantified before scale-up. The downstream pressure can be varied to obtain different thicknesses. Also, if the lab-scale equipment is automated using a robot hand, the synthesis will be more reproducible. It is also possible to imagine a scaled-up version of the set-up. It is shown in Figure 7.1, where a stationary and partially porous hollow metal cylinder can replace the porous metal plate used in the lab- scale apparatus. This equipment or a bigger lab-scale vacuum dip coating apparatus could be used to demonstrate the fabrication of a prototype spiral-wound membrane.

The work reported in this dissertation identified favorable support morphologies for a successful fabrication of the hybrid materials. But, the polymer supports were obtained as free samples. For scale-up, purchasing these supports from an external vendor may not be economically feasible. For this purpose, the pilot-scale casting machine can be used after its installation. Time devoted to fabricating the required supports in-house using polyethersulfone or polysulfone can help in moving this research forward.

In the final part of this work, zeolite/polymer hybrid materials were used as substrates for high permeance membranes. For this purpose, the quality of deposition

218 may need to be further improved. This can be done, as mentioned previously, by automating the vacuum dip-coating apparatus and also characterizing each batch of zeolite particles before coating. Variations in the sizes and size distribution of the particles can cause correponding variations in surface porosity and interparticulate pore size. If the polydispersity in the particles is substantial, the particle packing may be affected adversely, causing more cracks and defects to form. More attention should be paid to these aspects. Also, in order to further improve the performance and the adhesion at the zeolite-polymer interface, smaller particles are required.

In order to further increase the permeance of the amine-based selective layer, thickness can be reduced and/or carrier concentration can be increased. The results, however, will depend on the relative rates of reaction vs. mass transfer in the membrane.

In facilitated transport, forward and backward reactions take place at the membrane-feed and membrane-permeate interfaces, respectively. Also, there is diffusion of carrier-CO2 complexes across the membrane thickness. If the reactions are instantaneous, both the feed and permeate side reactions are at equilibrium with the respective interfaces, and the

CO2 permeance will depend on the equilibrium constants and carrier concentrations in addition to the diffusivities of CO2-carrier complexes and the membrane thickness. In this case, an inverse relationship with thickness is expected, and CO2 permeance will increase proportionally with thickness reduction.

If the reactions are not instantaneous relative to mass transfer, the reaction rates start playing a role in the net CO2 transport in addition to the gradients inside the membrane. In this case, rate constants enter the equations, and the dependence on the

219 membrane thickness reduces while the dependence on equilibrium constants and carrier concentrations change and become more complicated. This phenomenon is more probable in very thin membranes where the interfacial region is of the order of membrane thickness. The regime of transport will also depend on various other factors such as temperature, specific chemistry between CO2 and the carriers, size and structure of carrier molecules, etc., all of which can affect the competition between the reaction and diffusion. These aspects have been studied in detailed models for facilitated transport which can be used to understand the experimental data obtained in this work.161,162,163

That can, in turn, lead to better strategies for increasing membrane performance.

Experimentally, reducing the membrane thickness is fairly easy. The result, however, can be colored by unwanted effects of infiltration of coating solution into the substrate during membrane synthesis. Also, preparing very thin free-standing films may not be possible. In this context, modeling can also help in deciphering the extent to which penetration has affected the membrane performance. From a fabrication point of view, quantifying the penetration using cross-sectional images obtained by FIB-SEM may be helpful.

Although reducing the membrane thickness and/or increasing the carrier concentration can increase the membrane performance, it is important to remember their effects on membrane stability. Both these strategies can increase the chance of carrier leakage from the membrane during operation. Thus, there will be trade-off that can be found using experiments and modeling.

220

Lastly, the amine-based selective layer should be studied in more detail with

164 respect to its SO2 stability. Additives such as potassium citrate and/or others which can react reversibly with SO2 might provide a bypass for SO2 transport. This can reduce the chances of SO2 poisoning of amines. Also, the effect of temperature must be studied.

Directionally speaking, lowering the operating temperature should also reduce the rate of poisoning as observed by other researchers. This strategy will have to be combined with appropriate thickness reduction in order to achieve high CO2 permeance combined with good SO2 tolerance.

221

Non-porous

To Vacuum Pump Porous Hollow Stainless Steel Cylinder with a Sintered Bottom Section

Web

Roller

Coating Dispersion

Figure 7.1. Proposed continuous vacuum dip-coating set-up

222

APPENDIX A

APPENDICES TO CHAPTER 4

223

A.1 Cost metrics

% COE increase and capture cost are defined as follows: 81

COE COE % COE increase capture no capture 100 COEno capture

COEcapture COEno capture Capture cost ($/ton CO2 captured) CO2 captured

COE is based on the net power output of the plant. In this study, the net power output

(550 MW) has been kept the same for both the base plant and the plant with capture, which is consistent with other detailed cost studies.5, 81 The parasitic energy consumption, hypothetically, makes a power plant with capture larger than the one without capture for the same net power output. This also means that the untreated flue gas flow rate and consequently, the CO2 flow rate are higher for the plant with capture due to the additional fuel burnt to make-up the extra power. It is for the same reason that % COE increase is a more correct measure of the effect of capture integration on the plant economics.5 The capture cost, on the other hand, can underestimate the effect by normalizing the total cost to the total amount of CO2 captured which depends on the gross power output.

A.2 Compressor capital cost estimation

The compressor capital cost was obtained from the vendor estimate provided in

DOE report.5 The cost was normalized to the corresponding power consumption and

224 adjusted to $620/kW (2010 dollars) for a multi-stage centrifugal CO2 compressor, intercoolers and a drying system.

A.3 Make-up power unit cost estimation

The above cost analysis takes into account directly the capital costs (as TPI in

Table 4.2) and operating costs other than energy cost (components of VOM other than

MuPC in Table 4.2) related to the larger SAC facility. The make-up power cost (MuPC) held at $0.05/kWh includes indirectly the increased fuel costs for the power plant as well as the capital costs associated with the larger power plant (parts of the plant excluding the

SAC facility), which is explained as follows:

MuPC, defined as a unit cost in the preceding discussion, does not depend on the nature of the capture process. Thus, data reported by the DOE study for the SOTA amine process were used to deduce a reasonable value for MuPC. For a plant with capture with a net power output of 550 MW and using the SOTA amine process, the make-up power is equivalent to 222 MW.5 Out of the COE increase of 5.5 cents/kWh-net over the original

6.5 cents/kWh-net (85% increase), the following can be broken down for a larger SAC facility using the SOTA amine process:

Separation capital: 1.80 cents/kWh-net.

Compression capital: 0.21 cents/kWh-net.

Operating costs excluding energy and raw material cost of the SAC facility: 0.84

cents/kWh-net.

TS&M cost: 0.64 cents/kWh-net.

225

Since these costs have been accounted for directly in our analysis, we can deduct them from 5.5 cents/kWh-net to obtain a MuPC of 2.0 cents/kWh-net, which is equivalent to 2.0×550/222 = 4.955 cents/kWh of make-up power. A value of $0.05/kWh of make-up power was thus used.

A.4 Auxiliary power estimation

The effective parasitic energy consumption due to the SAC facility must also include the auxiliary power increase in parts of the power plant other than the facility itself. This also includes the circulating cooling water pump, cooling tower fan and other ground water pumps. For the SOTA amine process detailed in the DOE study with a total parasitic energy consumption of 222 MW, these numbers are as follows:

Auxiliary power increase in the power plant: 9.44 MW.

Power increase associated with circulating cooling water pumps, cooling tower fan and ground water pumps: 9.53 MW.

These numbers were normalized to the energy consumption/cooling water flow rate of the amine process and included appropriately in the cost calculation for the membrane process.

A.5 Comparison of cost model with the DOE cost estimation technique

To test the validity of the simple cost model used in this work, we applied it to the data in the DOE study. The following numbers were taken from that study for the SOTA amine process.

Fixed equipment cost without installation factor for the SAC facility: $247.4 million.

Cooling water cost: $1.3 million.

226

Raw material (specific to amine process): $2.2 million.

Parasitic energy consumption: 222 MW.

Using these numbers, assumptions and methodology outlined in Table 4.2 gives a

COE increase of 72.9%. If we take into account the important differences between our assumptions and the DOE study with respect to the labor cost ($15/hr in our study vs.

$34.65/hr in the DOE study), TS&M costs (4% in our study vs. 11.6% in the DOE study), the COE increase predicted by the simpler cost methodology used in this work is 83.1% vs. 85% in the detailed DOE study.

A.6 Steps in cost computation

1. Mass balance

Basis: 100 moles/sec of wet flue gas with the composition outlined in Table 4.1 for the power plant without capture.

From the amount of N2 in this gas (67.2 moles/sec), the air stream flow rate can be calculated as 85.9 moles/sec. In the plant with capture (Figure 4.1), all of the above air is used as sweep in the second membrane stage and is kept constant in all the cases.

Also, the recycled CO2 adds to the flue gas flow rate. This new flue gas flow rate

(Stream 1 in Figure 4.1) and the amount of recycled CO2 (Stream 5) can be found for different XCO2. Also, applying the CO2 recovery (90%) and purity (95% on dry basis) conditions, the flow rates and compositions (dry basis) of Streams 2 and 4 can be evaluated.

2. Membrane simulation

227

Using the above information, pressures, membrane selectivity and permeance, the system of differential equations outlined in Section 4.4.1 can be solved to obtain the first- stage membrane area along with the flow rate of Stream 3 and the water flow rate in

Stream 2. The equations were fed into the Partial Differential Equation (PDE) mode of

COMSOL Multiphysics which uses the finite element method. The domain (module length) as well as the dependent variables were non-dimensionalized and divided into 120 mesh elements. The result obtained was not influenced by further reduction in mesh size.

The predefined element type was Lagrange-quadratic.

It is important to highlight that during the above calculation of membrane area, selectivity or the permeate pressure, ps, were varied to obtain the 95% dry CO2 purity.

For a fixed pressure ratio, selectivity is obtained as an output of this simulation. For example, as given in Table 4.3, at XCO2 = 22.5%, pf = 1 bar and ps = 0.2 bar, a selectivity of 163 was obtained from the above simulation by trial and error. On the other hand, if the selectivity is increased to 200 for XCO2 = 22.5% and pf = 1 bar, ps can be increased to

0.224 bar (this simulation result, pf/ps = 4.5, is shown in Figure 4.4) by trial and error.

Both CO2 recovery and CO2 purity were adjusted within 0.05 percentage points in obtaining the area, selectivity and permeate pressures. These gave rise to the following uncertainties in the outputs of the above simulation.

Membrane area: ± 0.2%

Selectivity: ± 1.3%

Permeate pressure: ± 1.4%

228

For the second-stage membrane area, the stream 3 flow rate obtained from the above simulation, the stream 4 and air flow rates along with the amount of CO2 to be recycled in Stream 5 were fed into COMSOL Multiphysics. Because of air sweep, the transport in this stage is not limited by the pressure ratio. Thus, this stage area was not affected by the selectivity, and it had a similar uncertainty range as for the first stage.

3. Cost spreadsheet

Using the above membrane areas, pressures and flow rates, the % COE increase and capture cost can be calculated using the procedures outlined in Section 4.4.2 and the parameters defined in Table 4.2.

229

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