Computational Screening of MOF-Based Mixed Matrix Membranes for CO2/N2 Separations

Abstract

Atomically detailed simulations were used to examine CO2/N2 separation potential of metal organic framework- (MOF-) based mixed matrix membranes (MMMs) in this study. Gas permeability and selectivity of 700 new MMMs composed of 70 different MOFs and 10 different polymers were calculated for CO2/N2 separation. This is the largest number of MOF-based MMMs for which computational screening is done to date. Selecting the appropriate MOFs as filler particles in polymers resulted in MMMs that have higher CO2/N2 selectivities and higher CO2 permeabilities compared to pure polymer membranes. We showed that, for polymers that have low CO2 permeabilities but high CO2 selectivities, the identity of the MOF used as filler is not important. All MOFs enhanced the CO2 permeabilities of this type of polymers without changing their selectivities. Several MOF-based MMMs were identified to exceed the upper bound established for polymers. The methods we introduced in this study will create many opportunities to select the MOF/polymer combinations with useful properties for CO2 separation applications.