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

TitleIn silico discovery of metal-organic frameworks for precombustion CO2 capture using a genetic algorithm
Authors
Issue Date2016
Citation
Science Advances, 2016, v. 2, n. 10, article no. e1600909 How to Cite?
AbstractDiscovery of new adsorbent materials with a high CO2 working capacity could help reduce CO2 emissions from newly commissioned power plants using precombustion 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. We report the in silico discovery of highperforming adsorbents for precombustion CO2 capture by applying a genetic algorithm 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 a high CO2 working capacity and a high CO2/H2 selectivity. One of the synthesized MOFs shows a higher CO2 working capacity than any MOF reported in the literature under the operating conditions investigated here.
Persistent Identifierhttp://hdl.handle.net/10722/333263
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChung, Yongchul G.-
dc.contributor.authorGómez-Gualdrón, Diego A.-
dc.contributor.authorLi, Peng-
dc.contributor.authorLeperi, Karson T.-
dc.contributor.authorDeria, Pravas-
dc.contributor.authorZhang, Hongda-
dc.contributor.authorVermeulen, Nicolaas A.-
dc.contributor.authorStoddart, J. Fraser-
dc.contributor.authorYou, Fengqi-
dc.contributor.authorHupp, Joseph T.-
dc.contributor.authorFarha, Omar K.-
dc.contributor.authorSnurr, Randall Q.-
dc.date.accessioned2023-10-06T05:17:59Z-
dc.date.available2023-10-06T05:17:59Z-
dc.date.issued2016-
dc.identifier.citationScience Advances, 2016, v. 2, n. 10, article no. e1600909-
dc.identifier.urihttp://hdl.handle.net/10722/333263-
dc.description.abstractDiscovery of new adsorbent materials with a high CO2 working capacity could help reduce CO2 emissions from newly commissioned power plants using precombustion 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. We report the in silico discovery of highperforming adsorbents for precombustion CO2 capture by applying a genetic algorithm 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 a high CO2 working capacity and a high CO2/H2 selectivity. One of the synthesized MOFs shows a higher CO2 working capacity than any MOF reported in the literature under the operating conditions investigated here.-
dc.languageeng-
dc.relation.ispartofScience Advances-
dc.titleIn silico discovery of metal-organic frameworks for precombustion CO2 capture using a genetic algorithm-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1126/sciadv.1600909-
dc.identifier.scopuseid_2-s2.0-85015847607-
dc.identifier.volume2-
dc.identifier.issue10-
dc.identifier.spagearticle no. e1600909-
dc.identifier.epagearticle no. e1600909-
dc.identifier.eissn2375-2548-
dc.identifier.isiWOS:000387991500023-

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