Efficient Methods for Screening of Metal Organic Framework Membranes for Gas Separations Using Atomically Detailed Models

Abstract

Metal organic frameworks (MOFs) define a diverse class of nanoporous materials having potential applications in adsorption-based and membrane-based gas separations. We have previously used atomically detailed models to predict the performance of MOFs for membrane-based separations of gases, but these calculations require considerable computational resources and time. Here, we introduce an efficient approximate method for screening MOFs based on atomistic models that will accelerate the modeling of membrane applications. The validity of this approximate method is examined by comparison with detailed calculations for CH4/H2, CO2/CH4, and CO2/H2 mixtures at room temperature permeating through IRMOF-1 and CuBTC membranes. These results allow us to hypothesize a connection between two computationally efficient correlations predicting mixture adsorption and mixture self-diffusion properties and the validity of our approximate screening method. We then apply our model to six additional MOFs, IRMOF-8, -9, -10, and -14, Zn(bdc)(ted)0.5, and COF-102, to examine the effect of chemical diversity and interpenetration on the performance of metal organic framework membranes for light gas separations.