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Operando Electrochemical Spectroscopy for CO on Cu(100) at pH 1 to 13: Validation of Grand Canonical Potential Predictions

Baricuatro, Jack H. and Kwon, Soonho and Kim, Youn-Geun and Cummins, Kyle D. and Naserifar, Saber and Goddard, William A., III (2021) Operando Electrochemical Spectroscopy for CO on Cu(100) at pH 1 to 13: Validation of Grand Canonical Potential Predictions. ACS Catalysis, 11 (5). pp. 3173-3181. ISSN 2155-5435. doi:10.1021/acscatal.0c05564. https://resolver.caltech.edu/CaltechAUTHORS:20210225-152852499

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Abstract

Electrochemical reduction of CO₂ to value-added products is an attractive strategy to address issues of increasing atmospheric CO₂ concentration. Cu is the only pure metal catalyst known to electrochemically convert CO₂ to appreciable amounts of oxygenates and hydrocarbons such as C₂H₅OH, CH₄, and C₂H₄, but the Faraday efficiencies are too low and the onset potentials are too high. To discover electrocatalytic systems better than Cu, we use in silico strategies based on new grand canonical potential (GCP) methods, but the complexity of the electrode–electrolyte interface makes it difficult to validate the accuracy of GCP. Operando electrochemical polarization-modulation infrared spectroscopy (PMIRS) provides a performance benchmark for theoretical tools that account for the vibrational stretching frequencies of surface-bound CO, ν_(CO), as a function of pH and applied potential U. We show here that GCP calculations of the surface coverages of H*, OH*, and CO* on Cu(100) as a function of U lead to excellent predictions of the potential-dependent ν_(CO) and its shift with pH from 1 to 13. This validation justifies the use of GCP for predicting the performance of catalyst designs.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1021/acscatal.0c05564DOIArticle
ORCID:
AuthorORCID
Kwon, Soonho0000-0002-9225-3018
Kim, Youn-Geun0000-0002-5936-6520
Naserifar, Saber0000-0002-1069-9789
Goddard, William A., III0000-0003-0097-5716
Additional Information:© 2021 American Chemical Society. Received: December 18, 2020; Revised: February 8, 2021; Published: February 24, 2021. The invaluable contributions of Prof. Manuel P. Soriaga on the seriatim implementation of operando analytical protocols for CO₂ reduction studies are gratefully acknowledged. Manny passed away on July 17, 2019 and will always be missed in the electrochemical surface science community. The experimental portion of this paper is based upon work performed by the Joint Center for Artificial Photosynthesis, a DOE Energy Innovation Hub, supported through the Office of Science of the U.S. Department of Energy under Award No. DE-SC0004993. The computational studies were initiated with JCAP funding, but the final results in the figures are based on work performed by the Liquid Sunlight Alliance, which is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Fuels from Sunlight Hub under Award Number DE-SC0021266. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231. J.H.B. and S.K. first authorship is equally shared. The authors declare no competing financial interest.
Group:JCAP
Funders:
Funding AgencyGrant Number
Department of Energy (DOE)DE-SC0004993
Department of Energy (DOE)DE-SC0021266
Department of Energy (DOE)DE-AC02-05CH11231
Subject Keywords:operando electrochemical PMIRS, density functional theory, GCP, operando CO vibration frequencies
Other Numbering System:
Other Numbering System NameOther Numbering System ID
WAG1411
Issue or Number:5
DOI:10.1021/acscatal.0c05564
Record Number:CaltechAUTHORS:20210225-152852499
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210225-152852499
Official Citation:Operando Electrochemical Spectroscopy for CO on Cu(100) at pH 1 to 13: Validation of Grand Canonical Potential Predictions. Jack H. Baricuatro, Soonho Kwon, Youn-Geun Kim, Kyle D. Cummins, Saber Naserifar, and William A. Goddard. ACS Catalysis 2021 11 (5), 3173-3181; DOI: 10.1021/acscatal.0c05564
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:108223
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:26 Feb 2021 00:02
Last Modified:16 Nov 2021 19:10

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