RESUMEN
Metal-organic frameworks (MOFs) are highly tuneable, extended-network, crystalline, nanoporous materials with applications in gas storage, separations, and sensing. We review how molecular models and simulations of gas adsorption in MOFs have informed the discovery of performant MOFs for methane, hydrogen, and oxygen storage, xenon, carbon dioxide, and chemical warfare agent capture, and xylene enrichment. Particularly, we highlight how large, open databases of MOF crystal structures, post-processed to enable molecular simulations, are a platform for computational materials discovery. We discuss how to orient research efforts to routinise the computational discovery of MOFs for adsorption-based engineering applications.
RESUMEN
Decades of research have yet to yield porous adsorbents that meet the U.S. Department of Energy's methane storage targets. To better understand why, we calculated high-pressure methane adsorption in 600â¯000 randomly generated porous crystals, or "pseudomaterials," using atomistic grand canonical Monte Carlo (GCMC) simulations. These pseudomaterials were periodic configurations of Lennard-Jones spheres whose coordinates in space, along with corresponding well depths and radii, were all chosen at random. GCMC simulations were performed for pressures of 35 and 65 bar at a temperature of 298 K. Methane adsorption was compared for all materials against a range of other properties: average well depths and radii, number density, helium void fraction, and volumetric surface area. The results reveal structure-property relationships that resemble those previously observed for metal-organic frameworks and other porous materials. We contend that our computational methodology can be useful for discovering useful structure-property relationships related to gas adsorption without requiring experimentally accessible structural data.