Computational screening of metal-organic frameworks for membrane-based CO2/N-2/H2O separations: best materials for flue gas separation

Abstract

It has become a significant challenge to select the best metal-organic frameworks (MOFs) for membrane-based gas separations because the number of synthesized MOFs is growing exceptionally fast. In this work, we used high-throughput computational screening to identify the top MOF membranes for flue gas separation. Grand canonical Monte Carlo and molecular dynamics simulations were performed to assess adsorption and diffusion properties of CO2 and N-2 in 3806 different MOFs. Using these data, selectivities and permeabilities of MOF membranes were predicted and compared with those of conventional membranes, polymers, and zeolites. The best performing MOF membranes offering CO2/N-2 selectivity > 350 and CO2 permeability > 10(6 )Barrer were identified. Ternary CO2/N-2 /H2O mixture simulations were then performed for the top MOFs to unlock their potential under industrial operating conditions, and results showed that the presence of water decreases CO2/N-2 selectivity and CO2 permeability of some MOF membranes. As a result of this stepwise screening procedure, the number of promising MOF membranes to be investigated for flue gas separation in future experimental studies was narrowed down from thousands to tens. We finally examined the structure-performance relations of MOFs to understand which properties lead to the greatest promise for flue gas separation and concluded that lanthanide-based MOFs with narrow pore openings (<4.5 (A)under-circle), low porosities (<0.75), and low surface areas (<1000 m(2)/g) are the best materials for membrane-based CO2/N-2 separations.