Role of partial charge assignment methods in high-throughput screening of MOF adsorbents and membranes for CO2/CH4 separation

Metal organic frameworks (MOFs) have great potential for CO2 separation and there is a strong need to determine the best-performing MOFs due to the rapidly increasing number of materials. High-throughput computational screening of MOFs for CO2 separation has a tremendous value to identify the most promising MOF candidates to direct the experimental efforts to the best materials. Computational identification of promising MOF candidates using molecular simulations depends on the accurate description of electrostatic interactions between CO2 molecules and MOFs and computing these interactions requires partial charge assignment to MOF atoms. Quantum-chemistry based charge assignment methods are highly accurate but computationally expensive when very large numbers of MOFs are considered. Approximate methods can quickly define the charges of MOFs with less computational expense. In this work, we examined the role of partial charge assignment methods in high-throughput computational screening of MOFs for CO2/CH4 separation. A quantum based, density-derived electrostatic and chemical charge method (DDEC) and an approximate charge equilibration method (Qeq) were used to compute the adsorption of CO2/CH4 mixtures in 1500 MOFs under two different operating conditions. The results of molecular simulations utilizing different charge assignment methods were used to predict the performance evaluation metrics of MOF adsorbents and membranes. The results showed that although calculated metrics quantitatively varied depending on the method, the rankings of DDEC- and Qeq-charged MOFs based on individual performance metrics were highly correlated. On the other hand, the identity of the best performing MOF candidates was found to change based on the type of charge assignment method used in simulations.