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Experimentally refined crystal structures for metal− organic frameworks (MOFs) often include solvent molecules and partially occupied or disordered atoms. This creates a major impediment to applying high-throughput computational screening to MOFs. To address this problem, we have constructed a database of MOF structures that are derived from experimental data but are immediately suitable for molecular simulations. The computationready, experimental (CoRE) MOF database contains over 4700 porous structures with publically available atomic coordinates. Important physical and chemical properties including the surface area and pore dimensions are reported for these structures. To demonstrate the utility of the database, we performed grand canonical Monte Carlo simulations of methane adsorption on all structures in the CoRE MOF database. We investigated the structural properties of the CoRE MOFs that govern methane storage capacity and found that these relationships agree well with those derived recently from a large database of hypothetical MOFs.

Over 14 000 porous, three-dimensional metal–organic framework structures are compiled and analyzed as a part of an update to the Computation-Ready, Experimental Metal–Organic Framework Database (CoRE MOF Database). The updated database includes additional structures that were contributed by CoRE MOF users, obtained from updates of the Cambridge Structural Database and a Web of Science search, and derived through semiautomated reconstruction of disordered structures using a topology-based crystal generator. In addition, value is added to the CoRE MOF database through new analyses that can speed up future nanoporous materials discovery activities, including open metal site detection and duplicate searches. Crystal structures (only for the subset that underwent significant changes during curation), pore analytics, and physical property data are included with the publicly available CoRE MOF 2019 database.

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Analogous to the way the Human Genome Project advanced an array of biological sciences by mapping the human genome, the Materials Genome Initiative aims to enhance our understanding of the fundamentals of materials science by providing the information we need to accelerate the development of new materials.This approach is particularly applicable to recently developed classes of nanoporous materials, such as metal-organic frameworks (MOFs), which are synthesized from a limited set of molecular building blocks that can be combined to generate a very large number of different structures. In this Perspective, we illustrate how a materials genome approach can be used to search for high-performance adsorbent materials to store natural gas in a vehicular fuel tank. Drawing upon recent reports of large databases of existing and predicted nanoporous materials generated in silico, we have collected and compared on a consistent basis the methane uptake in over 650 000 materials based on the results of molecular simulation. The data that we have collected provide candidate structures for synthesis, reveal relationships between structural characteristics and performance, and suggest that it may be difficult to reach the current Advanced Research Project Agency-Energy (ARPA-E) target for natural gas storage. Broader contextNatural gas, mostly methane, is an attractive replacement for petroleum fuels for automotive vehicles because of its economic and environmental advantages. However, it suffers from a low volumetric energy density, necessitating densication to yield reasonable driving ranges from a full fuel tank. Densication strategies in the market today, liquefaction and compression, require expensive and cumbersome vehicular fuel tanks and rell station infrastructure. If we are able to develop a nanoporous adsorbent material to store natural gas at ambient temperature and moderate pressure, one could envision a simple fuel tank that can be relled at home. Modern, advanced nanoporous materials are highly tunable, inundating researchers with practically innite possibilities of materials to synthesize and test for methane storage. The current research is focused on nding among these millions of possible materials one that can be used to store natural gas without using liquefaction or compression processes. In this Perspective, we adopt a computational approach to screen databases of over 650 000 nanoporous material structures. Using this nanoporous materials genome approach, we reveal relationships between structural characteristics and performance, and suggest that it may be difficult, if not impossible, to reach the current Advanced Research Project Agency-Energy (ARPA-E) target for natural gas storage using nanoporous materials.