Large-scale screening of hypothetical metal–organic frameworks

Metal–organic frameworks (MOFs) are porous materials constructed from modular molecular building blocks, typically metal clusters and organic linkers. These can, in principle, be assembled to form an almost unlimited number of MOFs, yet materials reported to date represent only a tiny fraction of the possible combinations. Here, we demonstrate a computational approach to generate all conceivable MOFs from a given chemical library of building blocks (based on the structures of known MOFs) and rapidly screen them to find the best candidates for a specific application. From a library of 102 building blocks we generated 137,953 hypothetical MOFs and for each one calculated the pore-size distribution, surface area and methane-storage capacity. We identified over 300 MOFs with a predicted methane-storage capacity better than that of any known material, and this approach also revealed structure–property relationships. Methyl-functionalized MOFs were frequently top performers, so we selected one such promising MOF and experimentally confirmed its predicted capacity. Chemists are able to prepare a wide variety of metal–organic frameworks by connecting together inorganic and organic building blocks of all sorts of shapes and properties. Now, a large-scale computational screening approach that simulates thousands of hypothetical MOFs from previously synthesized ones can help identify just which materials should be pursued.