New Materials and Process Development for Energy-Efficient Carbon Capture in the Presence of Water Vapor

Transcription

1 New Materials and Process Development for Energy-Efficient Carbon Capture in the Presence of Water Vapor Randy Snurr, 1 Joe Hupp, 2 Omar Farha, 2 Fengqi You 1 1 Department of Chemical & Biological Engineering 2 Department of Chemistry Northwestern University, Evanston, IL

2 Increasing Atmospheric CO 2 Concentrations Level in 1832 from Antarctic ice cores: 284 ppm

3 Post-Combustion Carbon Capture and Sequestration World Resources Institute,

4 CO 2 Capture Goal: Remove CO 2 from flue gas exiting a power plant with minimal energy usage minimal operating costs minimal capital cost Currently, amine capture processes would cause ~80% increase in cost of electricity (COE). The DOE goal is 35%.

5 CO 2 Capture Flue gas is mainly N 2 CO 2 H 2 O Very challenging separation Very large flow rates: A 400 MW pulverized coal power plant produces 1,000,000 m 3 /h of flue gas 2,200,000 tons of CO 2 per year = 6000 tons per day Flue gas is at low pressure There are about 1100 coal-fired power plants in the U.S. and 5000 worldwide.

6 Adsorption Separations Adsorption separations are widely used in processes such as air separation PSA, TSA, VSA can be more energy efficient than traditional distillation separations A key issue is the choice of the adsorbent Novel adsorbent Nanotechnology for Carbon Dioxide Capture, R.R. Willis, A.I. Benin, R.Q. Snurr, A.O. Yazaydin, in Nanotechnology for the Energy Challenge, J. Garcia-Martinez, Ed., Wiley-VCH, 2010.

7 GCEP Project Started July 17, 2012 The goal of this project is to develop new materials and new adsorption process configurations for economical capture of 90% of CO 2 from flue gas, with a particular focus on circumventing or overcoming competitive adsorption of water. A critical premise of this work is that the sorbent material and the adsorption process must be developed together. This synergy is critical for our project. New materials may allow or even require new process configurations. Similarly, process design and development work may suggest new avenues, new design criteria, and new targets for materials synthesis and application. Team approach: Joe Hupp MOF synthesis, characterization, and testing Omar Farha MOF synthesis, characterization, and testing Randy Snurr molecular modeling and adsorption testing Fengqi You process modeling

8 Metal-Organic Frameworks MOFs Permanently porous, crystalline materials Metal or metal oxide nodes connected by organic linker molecules NU-100 Large surface areas (up to 7000 m 2 /g) and pore volumes Nodes and linkers can be tuned for desired purposes DO-MOF Mulfort, Farha, Stern, Sarjeant, and Hupp, J. Am. Chem. Soc., Fahra, Yazaydin, Eryazici, Malliakas, Hauser, Kanatzidis, Nguyen, Snurr, and Hupp, Nature Chem., 2010.

9 Metal-Organic Frameworks

10 Diversity of MOFs MOF-177 MIL-53 MOF-177 MIL-103 HKUST-1

11 Molecular Tinker Toys

12 Materials Design? Can tune material properties via synthesis pore size linker functionality open-metal sites extraframework cations or anions Can also modify MOFs after their synthesis

13 How Can We Rapidly Screen MOFs for CO 2 Capture? Combined Experimental and Computational Screening Identify candidate MOFs Obtain structure/property insights Model validation High-throughput Computational Screening

14 Screening MOFs for CO 2 Capture Experimental CO 2 uptake at 0.1 bar and 298 K M\DOBDC MOFs perform particularly well. MOFs with large free volume perform the worst at low pressure. MOFs having coordinatively unsaturated metal sites (open-metal sites) demonstrate the best performance. Yazaydin, Snurr, Park, Koh, Liu, LeVan, Benin, Jakubczak, Lanuza, Galloway, Low, Willis, J. Am. Chem. Soc., 2009.

15 Screening MOFs for CO 2 Capture No correlation with SA No correlation with free volume There is a strong correlation between CO 2 uptake and heat of adsorption at low pressure. Yazaydin et al., J. Am. Chem. Soc., 2009.

16 Simulation versus Experiment This diverse set of MOFs is a stringent test of simulation. Ranking from simulation is very close to that from experiment. The top 5 MOFs are correctly identified by the simulations. Experiment GCMC Mg-MOF Ni-MOF Co-MOF Zn-MOF Pd(2-pymo) HKUST UMCM-150(N 2 ) 7 9 UMCM MIL ZIF IRMOF UMCM MOF IRMOF

17 Molecular Tinker Toys

18 Virtual High-Throughput Screening Crystal generator for hypothetical MOFs Comprehensively enumerates all possible structures from a library of building blocks Creates a large database of hypothetical MOFs (over 137,000 entries and growing) Designed for high-throughput screening of physical properties Wilmer, Leaf, Lee, Farha, Hauser, Hupp, Snurr, Nature Chem., 2012.

19 Virtual High-Throughput Screening Real Hypothetical

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21 CH 4 adsorption (v(stp)/v) CH 4 adsorption (v(stp)/v) CH 4 adsorption (v(stp)/v) Finding Improved Methane Storage Materials Database restricted to MOFs with one type of node and one or two types of linkers 500 Monte Carlo cycles / MOF All 137k MOFs 2500 Monte Carlo cycles / MOF Top 7000 MOFs Monte Carlo cycles / MOF Top 350 MOFs Top 5% (7000 MOFs) Top 5% (350 MOFs) World record Hypothetical MOF Rank Hypothetical MOF Rank Hypothetical MOF Rank Wilmer, Leaf, Lee, Farha, Hauser, Hupp, Snurr, Nature Chem., 2012.

22 Structure-Property Relationships

23 hmofs.northwestern.edu Accessed by researchers in over 40 countries to date.

24 High-throughput Screening for CO 2 /N 2 Separations Used extended charge equilibration (EQeq) algorithm to obtain partial charges of framework atoms for over 137,000 structures Method avoids expensive quantum chemical calculations Method works with full periodic MOF structures Charges on all structures obtained in ~2 hours using 500 processors Ran CO 2 and N 2 pure component GCMC simulations at pressures relevant to VSA process for carbon capture from flue gas (as above) Wilmer, Kim, Snurr, J. Phys. Chem. Lett

25 Effect of Pore Size on Selectivity Wilmer, Farha, Bae, Hupp, Snurr, Energy & Environmental Science, in press.

26 Effect of the Heat of Adsorption

27 Can the Hypothetical MOFs Be Synthesized? Farha, Yazaydin, Eryazici, Malliakas, Hauser, Kanatzidis, Nguyen, Snurr, Hupp, Nature Chem., 2010.

28 How Can We Rapidly Screen MOFs for CO 2 Capture? Combined Experimental and Computational Screening (14 materials) Identify candidate MOFs Obtain structure/property insights Model validation High-throughput Computational Screening (137,000 materials)

29 Acknowledgments Screening of Existing MOFs for CO 2 Capture Dr. A. Özgür Yazaydin (U. Surrey) Dr. Krista Walton (Georgia Tech) Dr. Rich Willis (UOP) Dr. John Low (Argonne) Annabelle Benin (UOP) Prof. M. Doug LeVan (Vanderbilt U.) Prof. Stefano Bandani (U. Edinburgh) Prof. Adam Matzger (U. Michigan) Rapid Assessment Criteria Prof. Youn-Sang Bae (Yonsei University) High-throughput Computational Screening Chris Wilmer Dr. Ki Chul Kim Prof. Youn-Sang Bae (Yonsei University) Prof. Omar Farha Prof. Joe Hupp Funding GCEP Department of Energy Defense Threat Reduction Agency XSEDE Computing Resources NERSC Computing Resources

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31 New Materials and Process Development for Energy-Efficient Carbon Capture in the Presence of Water Vapor Randy Snurr, Joe Hupp, Omar Farha, Fengqi You 20 minutes plus 5-8 minutes for discussion

32 Five Adsorbent Evaluation Criteria for PSA or VSA Applications Subscripts: 1 = strong adsorbate (CO 2 ), 2 = weak adsorbate (N 2 ) N = uptake at partial pressure (considering the mixture condition) (1) CO 2 uptake at adsorption condition (mol/kg), N 1 ads (2) Working CO 2 capacity (mol/kg), N 1 = N 1 ads N 1 des (3) Regenerability (%), R = ( N 1 / N 1 ads ) 100 (4) Selectivity at adsorption condition, α 12 = (N 1 ads / N 2 ads ) (y 2 / y 1 ) y i = gas phase mole fraction of component i (5) Sorbent selection parameter, S = [(α 12 ads ) 2 / α 12 des ] ( N 1 / N 2 ) None of these criteria are perfect, but the criteria are complementary. Because only single-component isotherms of two gases at appropriate P and T ranges are required, these criteria can be easily calculated by material chemists to evaluate new materials.