Identifying promising metal-organic frameworks for heterogeneous catalysis via high-throughput periodic density functional theory.

Abstract

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. In this work, a fully automated, high-throughput periodic density functional theory (DFT) workflow for screening promising MOF candidates was developed and benchmarked, with a specific focus on applications in catalysis. As a proof-of-concept, we use the high-throughput workflow to screen MOFs containing open metal sites (OMSs) from the Computation-Ready, Experimental MOF database for the oxidative C-H bond activation of methane. The results from the screening process suggest that, despite the strong C-H bond strength of methane, the main challenge from a screening standpoint is the identification of MOFs with OMSs that can be readily oxidized at moderate reaction conditions. © 2019 Wiley Periodicals, Inc.