(147f) Identifying Promising Metal–Organic Frameworks for Methane Activation Via High-Throughput Periodic Density Functional Theory

Metal–organic frameworks (MOFs) are a class of nanoporous materials with highly tunable structures in terms of both chemical composition and topology. Due to their tunable nature, high-throughput computational screening is a particularly appealing method to reduce the time-to-discovery of MOFs with desirable physical and chemical properties. Recently, we have developed a fully automated, high-throughput periodic density functional theory (DFT) workflow for screening promising MOF candidates and applied it to a diverse set of experimentally derived MOFs with accessible metal sites for the oxidative activation of methane. We find that the thermodynamic favorability of forming the metal-oxo active site has a strong, inverse correlation with the reactivity toward C−H bond activation for a wide range of MOFs. This scaling relationship is found to hold over MOFs with varying coordination environments and metal compositions, provided the bonds of the framework atoms are conserved during the reaction. The need to conserve bonds is an important constraint on the correlations but also demonstrates a route to intentionally break the scaling relationship to generate novel catalytic reactivity. Periodic trends are also observed across the data set of screened MOFs, with later transition metals forming less stable but more reactive metal-oxo active sites. The results in this work provide robust rules-of-thumb for choosing MOFs to investigate for the activation of methane at moderate reaction conditions.