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

© 2019 Wiley Periodicals, Inc.

Bibliographische Detailangaben
Veröffentlicht in:Journal of computational chemistry. - 1984. - 40(2019), 12 vom: 05. Mai, Seite 1305-1318
1. Verfasser: Rosen, Andrew S (VerfasserIn)
Weitere Verfasser: Notestein, Justin M, Snurr, Randall Q
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2019
Zugriff auf das übergeordnete Werk:Journal of computational chemistry
Schlagworte:Journal Article Research Support, U.S. Gov't, Non-P.H.S. computational catalysis density functional theory high-throughput screening metal-organic frameworks methane activation
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520 |a 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 
650 4 |a Journal Article 
650 4 |a Research Support, U.S. Gov't, Non-P.H.S. 
650 4 |a computational catalysis 
650 4 |a density functional theory 
650 4 |a high-throughput screening 
650 4 |a metal-organic frameworks 
650 4 |a methane activation 
700 1 |a Notestein, Justin M  |e verfasserin  |4 aut 
700 1 |a Snurr, Randall Q  |e verfasserin  |4 aut 
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