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

Andrew S. Rosen; Justin M. Notestein; Randall Q. Snurr

doi:10.1002/jcc.25787

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

Andrew S. Rosen, Justin M. Notestein^*, Randall Q. Snurr

^*Corresponding author for this work

Chemical and Biological Engineering

Research output: Contribution to journal › Article › peer-review

89 Scopus citations

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.

Original language	English (US)
Pages (from-to)	1305-1318
Number of pages	14
Journal	Journal of computational chemistry
Volume	40
Issue number	12
DOIs	https://doi.org/10.1002/jcc.25787
State	Published - May 5 2019

Funding

A.S.R. acknowledges government support under contract FA9550-11-C-0028 and awarded by the Department of Defense, Air Force Office of Scientific Research, National Defense Science and Engineering Graduate (NDSEG) Fellowship, 32 CFR 168a. A.S.R. also gratefully acknowledges support from the Ryan Fellowship and the International Institute for Nanotechnology at Northwestern University. The material in this work is supported by the Institute for Catalysis in Energy Processes (ICEP) via the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Award Number DOE DE-FG02-03-ER15457. The authors acknowledge computing support through the resources and staff contributions provided for the Quest high-performance computing facility at Northwestern University, the Extreme Science and Engineering Discovery Environment (XSEDE) via Stampede2 at the Texas Advanced Computing Center, which is supported by National Science Foundation grant number ACI-1548562, and the DOD High Performance Computing Modernization Program at the Air Force Research Laboratory. The authors acknowledge Benjamin J. Bucior for assistance with setting up the potential energy grid calculations, Arun Gopalan for assistance with visualizing the potential energy grids, and Hieu A. Doan for useful discussions regarding transition state scaling relations. Contract Grant sponsor: U.S. Department of Defense; Contract Grant number: FA9550-11-C-0028; Contract Grant sponsor: National Science Foundation; Contract Grant number: ACI-1548562; Contract Grant sponsor: U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences; Contract Grant number: DOE DE-FG02-03-ER15457 A.S.R. acknowledges government support under contract FA9550-11-C-0028 and awarded by the Department of Defense, Air Force Office of Scientific Research, National Defense Science and Engineering Graduate (NDSEG) Fellowship, 32 CFR 168a. A.S.R. also gratefully acknowledges support from the Ryan Fellowship and the International Institute for Nanotechnology at Northwestern University. The material in this work is supported by the Institute for Catalysis in Energy Processes (ICEP) via the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Award Number DOE DE-FG02-03-ER15457. The authors acknowledge computing support through the resources and staff contributions provided for the Quest high-performance computing facility at Northwestern University, the Extreme Science and Engineering Discovery Environment (XSEDE)[99] via Stampede2 at the Texas Advanced Computing Center, which is supported by National Science Foundation grant number ACI-1548562, and the DOD High Performance Computing Modernization Program at the Air Force Research Laboratory. The authors acknowledge Benjamin J. Bucior for assistance with setting up the potential energy grid calculations, Arun Gopalan for assistance with visualizing the potential energy grids, and Hieu A. Doan for useful discussions regarding transition state scaling relations.

Keywords

computational catalysis
density functional theory
high-throughput screening
metal–organic frameworks
methane activation

ASJC Scopus subject areas

General Chemistry
Computational Mathematics

Access to Document

10.1002/jcc.25787

Cite this

@article{95c601b86f944b1a9a74f52a9930ad91,

title = "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.",

keywords = "computational catalysis, density functional theory, high-throughput screening, metal–organic frameworks, methane activation",

author = "Rosen, {Andrew S.} and Notestein, {Justin M.} and Snurr, {Randall Q.}",

note = "Publisher Copyright: {\textcopyright} 2019 Wiley Periodicals, Inc.",

year = "2019",

month = may,

day = "5",

doi = "10.1002/jcc.25787",

language = "English (US)",

volume = "40",

pages = "1305--1318",

journal = "Journal of computational chemistry",

issn = "0192-8651",

publisher = "John Wiley & Sons Inc.",

number = "12",

}

TY - JOUR

T1 - Identifying promising metal–organic frameworks for heterogeneous catalysis via high-throughput periodic density functional theory

AU - Rosen, Andrew S.

AU - Notestein, Justin M.

AU - Snurr, Randall Q.

PY - 2019/5/5

Y1 - 2019/5/5

N2 - 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.

AB - 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.

KW - computational catalysis

KW - density functional theory

KW - high-throughput screening

KW - metal–organic frameworks

KW - methane activation

UR - http://www.scopus.com/inward/record.url?scp=85061083421&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85061083421&partnerID=8YFLogxK

U2 - 10.1002/jcc.25787

DO - 10.1002/jcc.25787

M3 - Article

C2 - 30715733

AN - SCOPUS:85061083421

SN - 0192-8651

VL - 40

SP - 1305

EP - 1318

JO - Journal of computational chemistry

JF - Journal of computational chemistry

IS - 12

ER -

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

Abstract

Funding

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this