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High-throughput computational screening of metal organic frameworks (MOFs) enables the discovery of new promising materials for CO 2 capture and H 2 purification. The number of synthesized MOFs is increasing very rapidly, and computation-ready, experimental MOF databases are being updated. Screening the most recent MOF database is essential to identify the best performing materials among several thousands. In this work, we performed molecular simulations of the most recent MOF database and described both the adsorbent and membrane-based separation performances of 10 221 MOFs for CO 2 capture and H 2 purification. The best materials identified for pressure swing adsorption, vacuum swing adsorption, and temperature swing adsorption processes outperformed commercial zeolites and previously studied MOFs in terms of CO 2 selectivity and adsorbent performance score. We then discussed the applicability of Ideal Adsorbed Solution Theory (IAST), effects of inaccessible local pores and catenation in the frameworks and the presence of impurities in CO 2 /H 2 mixture on the adsorbent performance metrics of MOFs. Very large numbers of MOF membranes were found to outperform traditional polymer and porous membranes in terms of H 2 permeability. Our results show that MOFs that are recently added into the updated MOF database have higher CO 2 /H 2 separation potentials than the previously reported MOFs. MOFs with small pores were identified as potential adsorbents for selective capture of CO 2 from H 2 , whereas MOFs with high porosities were the promising membranes for selective separation of H 2 from CO 2 . This study reveals the importance of enriching the number of MOFs in high-throughput computational screening studies for the discovery of new promising materials for CO 2 /H 2 separation.

Do New MOFs Perform Better for CO2 Capture and H2 Purification? Computational Screening of the Updated MOF Database

Do New MOFs Perform Better for CO₂ Capture and H₂ Purification? Computational Screening of the Updated MOF Database