High-Throughput Screening of the CoRE-MOF-2019 Database for CO 2 Capture from Wet Flue Gas: A Multi-Scale Modeling Strategy.

Stabilizing the escalating CO 2 levels in the atmosphere is 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 CO 2 from point source emissions using solid adsorbents may play a part in meeting this challenge, and metal-organic frameworks (MOFs) are considered to be a promising class of materials for this purpose. It is important to consider the co-adsorption of water when designing materials for CO 2 capture from post-combustion flue gases. Computational high-throughput screening (HTS) is a powerful tool to identify top-performing candidates for a particular application from a large material database. Using a multi-scale modeling strategy that includes a machine learning model, density functional theory (DFT) calculations, force field (FF) optimization, and grand canonical Monte Carlo (GCMC) simulations, we carried out a systematic computational HTS of the all-solvent-removed version of the computation-ready experimental metal-organic framework (CoRE-MOF-2019) database for selective adsorption of CO 2 from a wet flue gas mixture. After initial screening based on the pore diameters, a total of 3703 unique MOFs from the database were considered for screening based on the FF interaction energies of CO 2 , N 2 , and H 2 O molecules with the MOFs. MOFs showing stronger interactions with CO 2 compared to that with H 2 O and N 2 were considered for the next level of screening based on the interaction energies calculated from DFT. CO 2 -selective MOFs from DFT screening were further screened using two-component (CO 2 and N 2 ) and finally three-component (CO 2 , N 2 , and H 2 O) GCMC simulations to predict the CO 2 capacity and CO 2 /N 2 selectivity. Our screening study identified MOFs that show selective CO 2 adsorption under wet flue gas conditions with significant CO 2 uptake capacity and CO 2 /N 2 selectivity in the presence of water vapor. We also analyzed the nature of pore confinements responsible for the observed CO 2 selectivity.