Abstract:
:Discovery 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 high-performing 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.
journal_name
Sci Advjournal_title
Science advancesauthors
Chung YG,Gómez-Gualdrón DA,Li P,Leperi KT,Deria P,Zhang H,Vermeulen NA,Stoddart JF,You F,Hupp JT,Farha OK,Snurr RQdoi
10.1126/sciadv.1600909subject
Has Abstractpub_date
2016-10-14 00:00:00pages
e1600909issue
10issn
2375-2548pii
1600909journal_volume
2pub_type
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