Classical Density Functional Theory as a Fast and Accurate Method for Adsorption Property Prediction of Porous Materials

Physical adsorption separation is vital for many industrial processes, prompting researchers to develop new materials for energy-efficient processes. Porous adsorbent materials are of particular interest due to their diverse design possibilities and computational screening has accelerated the search for optimal materials. Classical density functional theory (cDFT) has recently been used as a faster alternative to state-of-the-art computational methods for screening of porous materials. However, extensive validation of cDFT predictions has not been performed for many materials, in a wide range of conditions, and with guest molecules exhibiting strong Coulombic interactions. In this paper, we validate the cDFT predictions by calculating the adsorption properties for more than 500 Metal-Organic Frameworks with three adsorbate molecules (CH4, N2, and CO2) and comparing them to state-of-the-art results from Grand Canonical Monte Carlo (GCMC) simulations. For CO2, we introduce the computation of Coulombic interactions between the MOF and the molecule, which are necessary to accurately describe this system. Our results demonstrate cDFT's ability to accurately replicate GCMC adsorption isotherms and enthalpies of adsorption while needing a median time of only 6 minutes per material. These features position cDFT as a serious candidate for adsorption properties estimations of porous materials for a wide range of physical adsorption-based processes.