CO2/N2 Selectivity Prediction in Supported Ionic Liquid Membranes (SILMs) by COSMO-RS

Abstract

The quantum chemical COSMO-RS method was applied to describe supported ionic liquid membranes (SILMs) with an enhanced capacity of selective separation of CO2 from N2, in order to contribute to the design of CO2 postcombustion capture technologies based on ionic liquid (IL) solvents. First, the predictive capability of the COSMO-RS method was evaluated through a comparison with a wide range of selectivity experimental data, and a further optimization based on the Henry’s Law constant of each solute in ILs was developed to improve the prediction of CO2/N2 selectivity in SILMs. Afterward, the optimized COSMO-RS approach was applied to design suitable SILM systems for CO2/N2 separation by driving a computational screening of 224 ILs, with results illustrating the capability of [SCN−]-based ILs to enhance the selective separation of CO2 from N2. Finally, to better understand SILM behavior in CO2 separation, the CO2/N2 selectivity differences among ILs were successfully related to the excess enthalpy of CO2−IL and N2−IL mixtures in solution predicted by COSMO-RS. In addition, the intermolecular interactions (electrostatic, hydrogen bonding, and van der Waals) between CO2−IL and N2−IL systems in the liquid phase, quantified by COSMO-RS, were analyzed in order to contribute to the rational selection of SILMs with positive characteristics for CO2/N2 selective separation.