Efficient Prediction of Multicomponent Adsorption Isotherms and Enthalpies of Adsorption in MOFs Using Classical Density Functional Theory

We demonstrate that classical density functional theory (DFT) based on the PC-SAFT equation of state is a fast, accurate, and predictive model to predict multicomponent adsorption in porous materials, which is an essential step toward the design of next-generation adsorbents for relevant applications. Using GPU acceleration, adsorption isotherms and adsorption enthalpies can be obtained in a matter of seconds, which is several orders of magnitude faster than grand canonical Monte Carlo (GCMC) simulations. Using metal-organic frameworks as adsorbents and non- or weakly polar molecules as adsorbates, we validate our approach by performing GCMC simulations for binary, ternary, and quaternary mixtures with practically relevant applications, such as noble gas separations (Kr/Xe, Ar/Kr/Xe), direct dry air capture (CO₂/N₂), hydrogen enrichment (CH₄/H₂, CH₄/H₂/N₂) and adsorbed natural gas (CH₄/C₃H₈, CH₄/C₂H₆/C₃H₈, CH₄/C₂H₆/C₃H₈/N₂). Classical DFT reproduces loadings and adsorption enthalpies of the mixtures in close agreement with results from GCMC simulations. Thus, classical DFT expands our toolbox for studying multicomponent adsorption.