Gas adsorption and separation in metal-organic frameworks by PC-SAFT based density functional theory

In this work, we examine the theoretical performance of perturbed-chain statistical associating fluid theory based density functional theory (DFT) in predicting gas adsorption and separation in metal-organic frameworks by using simulation and experimental data as the benchmark. Adsorption isotherms of methane and ethane in pure gas and mixtures and selectivities for ethane/methane mixtures are calculated. The predicted isotherms by DFT are in excellent agreement with simulation and experimental data for pure methane and ethane, whereas for the mixture, DFT is in semi-quantitative accordance with simulation results. For fast and high-throughput screening of material purpose, three algorithms including Picard iteration with line search, Anderson mixing, and Picard-Anderson-hybrid algorithm are proposed to calculate the three dimensional density distribution of confined gases. The advantages and limitations of the three algorithms under various conditions are discussed.