Modeling Multicomponent Gas Adsorption in Nanoporous Materials with Two Versions of Nonlocal Classical Density Functional Theory

Two versions of nonlocal classical density functional theory (cDFT) have been proposed to predict multicomponent gas adsorption in nanoporous materials by using the Lennard-Jones model for gas mixtures and the universal force field for the adsorbents. With the modified fundamental measure theory to describe short-range repulsions or volume-exclusion effects, one version of cDFT adopts the mean-field approximation for van der Waals attraction (here referred to as cDFT-MFA) as commonly used in porous material characterization, and the other version accounts for long-range correlations through a weighted-density approximation (cDFT-WDA). For a number of gas mixtures in MOF-5 (without sub-pores inaccessible to gas molecules), the adsorption isotherms predicted from cDFT-WDA are quantitatively consistent with results from grand canonical Monte Carlo simulation, while cDFT-MFA systematically underestimates the adsorption due to the neglect of correlation effects. Nevertheless, both versions of cDFT outperform the ideal adsorbed solution theory (IAST) at high pressure. Because IAST predicts mixture adsorption using only single-component data, it fails to capture the selective behavior arising from asymmetric interactions among different chemical species. The cDFT calculations are implemented with massively parallel GPU-accelerated algorithms to achieve rapid yet accurate predictions of multicomponent adsorption isotherms with full atomistic details of the adsorbent materials. This work thus provides a theoretical basis for the computational design of adsorption-based separation processes as well as for screening and data-driven inverse design of nanoporous materials.