期刊
ACS APPLIED MATERIALS & INTERFACES
卷 15, 期 23, 页码 28084-28092出版社
AMER CHEMICAL SOC
DOI: 10.1021/acsami.3c04079
关键词
CO2 adsorption; density functional theory; metal-organic framework; MOF; MonteCarlo simulation
Stabilizing the increasing CO2 levels in the atmosphere is a grand challenge. Metal-organic frameworks (MOFs) are considered promising materials for capturing CO2 from emissions. Considering the co-adsorption of water is important when designing materials for CO2 capture from post-combustion flue gases.
Stabilizing the escalating CO2 levels in theatmosphereis a grand challenge in view of the increasing global demand for energy,the majority of which currently comes from the burning of fossil fuels.Capturing CO2 from point source emissions using solid adsorbentsmay play a part in meeting this challenge, and metal-organicframeworks (MOFs) are considered to be a promising class of materialsfor this purpose. It is important to consider the co-adsorption ofwater when designing materials for CO2 capture from post-combustionflue gases. Computational high-throughput screening (HTS) is a powerfultool to identify top-performing candidates for a particular applicationfrom a large material database. Using a multi-scale modeling strategythat includes a machine learning model, density functional theory(DFT) calculations, force field (FF) optimization, and grand canonicalMonte Carlo (GCMC) simulations, we carried out a systematic computationalHTS of the all-solvent-removed version of the computation-ready experimentalmetal-organic framework (CoRE-MOF-2019) database for selectiveadsorption of CO2 from a wet flue gas mixture. After initialscreening based on the pore diameters, a total of 3703 unique MOFsfrom the database were considered for screening based on the FF interactionenergies of CO2, N-2, and H2O moleculeswith the MOFs. MOFs showing stronger interactions with CO2 compared to that with H2O and N-2 were consideredfor the next level of screening based on the interaction energiescalculated from DFT. CO2-selective MOFs from DFT screeningwere further screened using two-component (CO2 and N-2) and finally three-component (CO2, N-2, and H2O) GCMC simulations to predict the CO2 capacity and CO2/N-2 selectivity. Our screeningstudy identified MOFs that show selective CO2 adsorptionunder wet flue gas conditions with significant CO2 uptakecapacity and CO2/N-2 selectivity in the presenceof water vapor. We also analyzed the nature of pore confinements responsiblefor the observed CO2 selectivity.
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