Title: Ab Initio Prediction of Adsorption Selectivities for Binary Gas Mixtures on a Heterogeneous Metal–Organic Framework Surface

Authors: Kaido Sillar, Arpan Kundu, Joachim Sauer

DOI: https://doi.org/10.1021/acs.jpcc.3c02494

Abstract: Grand canonical Monte Carlo simulations on a lattice of adsorption sites (L-GCMC) are performed for prediction of adsorption selectivities for three binary mixtures, CO2/CH4, CO2/N2, and CH4/N2, in the metal–organic framework Mg2(dobdc), also known as CPO-27-Mg or Mg-MOF-74. Based on L-GCMC simulated pure gas adsorption data, we evaluated the performance of IAST in conditions where the adsorbed phase is nonideal due to substantial interaction between adsorbed molecules and heterogeneity of adsorption sites. The selectivity for CO2 adsorption from the CO2/CH4 mixture reaches the maximum of 290 at 298 K and at subatmospheric pressures when mainly the Mg2+ sites get populated. For the CO2/N2 mixture, with increasing surface coverage up to completing the monolayer, the CO2 adsorption selectivity continuously increases up to 800. This shows that for that mixture, the selectivity is not the highest for the open metal sites but for adsorption on Linker sites. Compared to L-GCMC results, the selectivities predicted by IAST are underestimated for subatmospheric pressures for the CO2/CH4 mixture and for almost the full pressure range for the CO2/N2 mixture. Thus, IAST predicted selectivities are less accurate if the adsorbed phase is not ideal, and the real material can be a much better adsorbent for gas separation than predicted by IAST.