In silico discovery of metal-organic frameworks for precombustion CO2 capture using a genetic algorithm

Chung, Y. G.; Gomez-Gualdron, D. A.; Li, P.; Leperi, K. T.; Deria, P.; Zhang, H.; Vermeulen, N. A.; Stoddart, J. F.; You, F.; Hupp, J. T.; Farha, O. K.; Snurr, R. Q.

doi:10.1126/sciadv.1600909

Title: In silico discovery of metal-organic frameworks for precombustion CO₂ capture using a genetic algorithm

Journal Article · Fri Oct 14 00:00:00 EDT 2016 · Science Advances

DOI:https://doi.org/10.1126/sciadv.1600909· OSTI ID:1468797

Chung, Y. G. ^[1]; Gomez-Gualdron, D. A. ^[2]; Li, P. ^[3]; Leperi, K. T. ^[1]; Deria, P. ^[3]; Zhang, H. ^[1]; Vermeulen, N. A. ^[3]; Stoddart, J. F. ^[3]; You, F. ^[1]; Hupp, J. T. ^[3]; Farha, O. K. ^[4]; Snurr, R. Q. ^[1]

Northwestern Univ., Evanston, IL (United States). Dept. of Chemical and Biological Engineering
Northwestern Univ., Evanston, IL (United States). Dept. of Chemical and Biological Engineering; Colorado School of Mines, Golden, CO (United States). Dept. of Chemical and Biological Engineering
Northwestern Univ., Evanston, IL (United States). Dept. of Chemistry
Northwestern Univ., Evanston, IL (United States). Dept. of Chemistry; King Abdulaziz Univ., Jeddah (Saudi Arabia)

Discovery of new adsorbent materials with large CO2 working capacity could help reduce CO2 emissions from newly commissioned power plants using pre-combustion carbon capture. High-throughput computational screening efforts can accelerate the discovery of new adsorbents but sometimes require significant computational resources to explore the large space of possible materials. Here, we report in silico discovery of high-performing adsorbents for pre-combustion CO2 capture by applying a genetic algorithm (GA) to efficiently search a large database of metal-organic frameworks (MOFs) for top candidates. High-performing MOFs identified from the in silico search were synthesized and activated and show high CO2 working capacity and CO2/H2 selectivity. One of the synthesized MOFs shows a higher CO2 working capacity than any MOF reported in the literature at the operating conditions investigated here.

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Research Organization:: Univ. of Minnesota, Minneapolis (United States); Northwestern Univ., Evanston, IL (United States); Nanoporous Materials Genome Center

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES). Chemical Sciences, Geosciences, and Biosciences Division

Grant/Contract Number:: SC0008688; FG02-08ER15967; FG02-12ER16362

OSTI ID:: 1468797

Alternate ID(s):: OSTI ID: 1476385

Journal Information:: Science Advances, Vol. 2, Issue 10; ISSN 2375-2548

Publisher:: AAASCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 198 works

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genetic algorithm
high-throughput material screening
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Title: In silico discovery of metal-organic frameworks for precombustion CO2 capture using a genetic algorithm

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Title: In silico discovery of metal-organic frameworks for precombustion CO₂ capture using a genetic algorithm