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Quantitative Phase Field Model for Electrochemical Systems

delete2023-12-07
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OA
AI
J
Jin Zhang *
A
Alexander F. Chadwick
P
Peter W. Voorhees
DOI:10.1149/1945-7111/ad0ff6delete
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摘要

摘要

En 中文
Modeling microstructure evolution in electrochemical systems is vital for understanding the mechanism of various electrochemical processes. In this work, we propose a general phase field framework that is fully variational and thus guarantees that the energy decreases upon evolution in an isothermal system. The bulk and interface free energies are decoupled using a grand potential formulation to enhance numerical efficiency. The variational definition of the overpotential is used, and the reaction kinetics is incorporated into the evolution equation for the phase field to correctly capture capillary effects and eliminate additional model parameter calibrations. A higher-order kinetic correction is derived to accurately reproduce general reaction models such as the Butler-Volmer, Marcus, and Marcus-Hush-Chidsey models. Electrostatic potentials in the electrode and the electrolyte are considered separately as independent variables, providing additional freedom to capture the interfacial potential jump. To handle realistic materials and processing parameters for practical applications, a driving force extension method is used to enhance the grid size by three orders of magnitude. Finally, we comprehensively verify our phase field model using classical electrochemical theory. Quantitative simulation of electrochemical processes with evolving interfacesPhase field model based on nonequilibrium/irreversible thermodynamicsPhase field model with general thermodynamics and kineticsNumerical efficient simulation with realistic materials parameters and system size
Keyword:
Batteries-Lithium
Electrodeposition
Electrodeposition-modeling
Energy Storage
Energy Conversion
Thermodynamics
Theory and Modelling

期刊

Journal of the Electrochemical Society 封面图
Journal of the Electrochemical Society
IF:
3.3
论文数:
3.3W
被引数:
9.4W

机构

N
Northwestern University
学者数:
6.2W
论文数: 5.3W
被引数: 3.9K
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