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Title: Assessing Correlations of Perovskite Catalytic Performance with Electronic Structure Descriptors

Abstract

Electronic structure descriptors are computationally efficient quantities used to construct qualitative correlations for a variety of properties. In particular, the oxygen p-band center has been used to guide material discovery and fundamental understanding of an array of perovskite compounds for use in catalyzing the oxygen reduction and evolution reactions. Yet, an assessment of the effectiveness of the oxygen p-band center at predicting key measures of perovskite catalytic activity has not been made and would be highly beneficial to guide future predictions and codify best practices. In this work, we have used density functional theory at the Perdew–Burke–Ernzerhof (PBE), PBEsol, PBE + U, strongly constrained and appropriately normed functional, and Heyd–Scuseria–Ernzerhof (HSE06) levels to assess the correlations of numerous measures of catalytic performance for a series of technologically relevant perovskite oxides, using the bulk oxygen p-band center as an electronic structure descriptor. We have analyzed correlations of the calculated oxygen p-band center for all considered functionals with the experimentally measured X-ray emission spectroscopy oxygen p-band center and multiple measures of catalytic activity, including high-temperature oxygen reduction surface exchange rates, aqueous oxygen evolution current densities, and binding energies of oxygen evolution intermediate species. Our findings show that the best correlations for allmore » measures of catalytic activity considered here are made with PBE-level calculations, with strong observed linear correlations with the bulk oxygen p-band center (R2 = 0.81–0.87). This study illustrates that strong linear correlations between numerous important measures of catalytic activity and the oxygen p-band bulk descriptor can be obtained under a consistent computational framework, and these correlations can serve as a guide for future experiments and simulations for development of perovskite and related oxide catalysts.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [1]
  1. Univ. of Wisconsin−Madison, Madison, WI (United States)
  2. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Org.:
USDOE; University of Wisconsin–Madison Center For High Throughput Computing (CHTC)
OSTI Identifier:
1543616
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Chemistry of Materials
Additional Journal Information:
Journal Volume: 31; Journal Issue: 3; Journal ID: ISSN 0897-4756
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY

Citation Formats

Jacobs, Ryan, Hwang, Jonathan, Shao-Horn, Yang, and Morgan, Dane. Assessing Correlations of Perovskite Catalytic Performance with Electronic Structure Descriptors. United States: N. p., 2019. Web. doi:10.1021/acs.chemmater.8b03840.
Jacobs, Ryan, Hwang, Jonathan, Shao-Horn, Yang, & Morgan, Dane. Assessing Correlations of Perovskite Catalytic Performance with Electronic Structure Descriptors. United States. https://doi.org/10.1021/acs.chemmater.8b03840
Jacobs, Ryan, Hwang, Jonathan, Shao-Horn, Yang, and Morgan, Dane. Fri . "Assessing Correlations of Perovskite Catalytic Performance with Electronic Structure Descriptors". United States. https://doi.org/10.1021/acs.chemmater.8b03840. https://www.osti.gov/servlets/purl/1543616.
@article{osti_1543616,
title = {Assessing Correlations of Perovskite Catalytic Performance with Electronic Structure Descriptors},
author = {Jacobs, Ryan and Hwang, Jonathan and Shao-Horn, Yang and Morgan, Dane},
abstractNote = {Electronic structure descriptors are computationally efficient quantities used to construct qualitative correlations for a variety of properties. In particular, the oxygen p-band center has been used to guide material discovery and fundamental understanding of an array of perovskite compounds for use in catalyzing the oxygen reduction and evolution reactions. Yet, an assessment of the effectiveness of the oxygen p-band center at predicting key measures of perovskite catalytic activity has not been made and would be highly beneficial to guide future predictions and codify best practices. In this work, we have used density functional theory at the Perdew–Burke–Ernzerhof (PBE), PBEsol, PBE + U, strongly constrained and appropriately normed functional, and Heyd–Scuseria–Ernzerhof (HSE06) levels to assess the correlations of numerous measures of catalytic performance for a series of technologically relevant perovskite oxides, using the bulk oxygen p-band center as an electronic structure descriptor. We have analyzed correlations of the calculated oxygen p-band center for all considered functionals with the experimentally measured X-ray emission spectroscopy oxygen p-band center and multiple measures of catalytic activity, including high-temperature oxygen reduction surface exchange rates, aqueous oxygen evolution current densities, and binding energies of oxygen evolution intermediate species. Our findings show that the best correlations for all measures of catalytic activity considered here are made with PBE-level calculations, with strong observed linear correlations with the bulk oxygen p-band center (R2 = 0.81–0.87). This study illustrates that strong linear correlations between numerous important measures of catalytic activity and the oxygen p-band bulk descriptor can be obtained under a consistent computational framework, and these correlations can serve as a guide for future experiments and simulations for development of perovskite and related oxide catalysts.},
doi = {10.1021/acs.chemmater.8b03840},
journal = {Chemistry of Materials},
number = 3,
volume = 31,
place = {United States},
year = {Fri Jan 04 00:00:00 EST 2019},
month = {Fri Jan 04 00:00:00 EST 2019}
}

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