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Grand canonical electronic density-functional theory: Algorithms and applications to electrochemistry

Sundararaman, Ravishankar and Goddard, William A., III and Arias, Tomas A. (2017) Grand canonical electronic density-functional theory: Algorithms and applications to electrochemistry. Journal of Chemical Physics, 146 (11). Art. No. 114104. ISSN 0021-9606. doi:10.1063/1.4978411.

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First-principles calculations combining density-functional theory and continuum solvation models enable realistic theoretical modeling and design of electrochemical systems. When a reaction proceeds in such systems, the number of electrons in the portion of the system treated quantum mechanically changes continuously, with a balancing charge appearing in the continuum electrolyte. A grand-canonical ensemble of electrons at a chemical potential set by the electrode potential is therefore the ideal description of such systems that directly mimics the experimental condition. We present two distinct algorithms: a self-consistent field method and a direct variational free energy minimization method using auxiliary Hamiltonians (GC-AuxH), to solve the Kohn-Sham equations of electronic density-functional theory directly in the grand canonical ensemble at fixed potential. Both methods substantially improve performance compared to a sequence of conventional fixed-number calculations targeting the desired potential, with the GC-AuxH method additionally exhibiting reliable and smooth exponential convergence of the grand free energy. Finally, we apply grand-canonical density-functional theory to the under-potential deposition of copper on platinum from chloride-containing electrolytes and show that chloride desorption, not partial copper monolayer formation, is responsible for the second voltammetric peak.

Item Type:Article
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URLURL TypeDescription Paper
Sundararaman, Ravishankar0000-0002-0625-4592
Goddard, William A., III0000-0003-0097-5716
Arias, Tomas A.0000-0001-5880-0260
Additional Information:© 2017 AIP Publishing LLC. (Received 16 January 2017; accepted 27 February 2017; published online 16 March 2017) R.S. and W.A.G. acknowledge support from the Joint Center for Artificial Photosynthesis (JCAP), a DOE Energy Innovation Hub, supported through the Office of Science of the U.S. Department of Energy under Award No. DE-SC0004993. R.S. and T.A.A. acknowledge support from the Energy Materials Center at Cornell (EMC^2), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Award No. DE-SC0001086. Calculations in this work used the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. We thank Kendra Letchworth-Weaver, Kathleen Schwarz, Yuan Ping, Hai Xiao, Tao Cheng, Robert J. Nielsen, and Jason Goodpaster for insightful discussions.
Funding AgencyGrant Number
Department of Energy (DOE)DE-SC0004993
Department of Energy (DOE)DE-SC0001086
Department of Energy (DOE)DE-AC02-05CH11231
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Issue or Number:11
Record Number:CaltechAUTHORS:20170316-155448902
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:75188
Deposited By: George Porter
Deposited On:17 Mar 2017 14:59
Last Modified:15 Nov 2021 16:31

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