High-Throughput Screening of Metal Organic Frameworks as Fillers in Mixed Matrix Membranes for Flue Gas Separation

High-throughput computational screening of metal organic frameworks (MOFs) is performed to evaluate their performances as fillers in mixed matrix membranes (MMMs). Grand canonical Monte Carlo and molecular dynamics simulations are performed to calculate CO2 and N-2 permeabilities of 7822 synthesized MOFs. This data are then combined with the experimentally reported gas permeability data of 14 different polymers using a theoretical permeation model. As a result, CO2 permeabilities and CO2/N-2 selectivities of 109 508 different types of MOF-based MMMs are estimated. The maximum CO2/N-2 selectivity and CO2 permeability of MOF/polymer MMMs are computed as 64.3 and 36 103 Barrer, respectively. The top 50 MOFs that significantly improve CO2/N-2 separation performances of highly permeable polymers are identified and their potentials for separation of binary CO2/N-2 mixture are examined at practical operating conditions. Results show that several MOFs offer significant improvements both in the gas permeability and selectivity of polymers when used as fillers in MMMs for flue gas separation. The MOF structure-membrane performance relations are also investigated for MOF/polymer MMMs, and results show that MOFs with narrow pore sizes (3.75-5.12 angstrom), low surface areas (<1000 m(2) g(-1)), and moderate porosities (0.41-0.58) lead to highly selective MMMs.