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Protocol for phase-field simulations of lithium dendrite growth with MOOSE framework

Phase-field simulation is a powerful tool for understanding lithium metal electrodeposition. This protocol outlines the process of numerically solving the phase-field equations using the MOOSE framework. Here, we describe steps to obtain the spatiotemporal distribution of major physical characterist...

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Detalles Bibliográficos
Autores principales: Jin, Shoutong, Wu, Yongjun, Yang, Hui, Huang, Yuhui, Hong, Zijian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9508604/
https://www.ncbi.nlm.nih.gov/pubmed/36149793
http://dx.doi.org/10.1016/j.xpro.2022.101713
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author Jin, Shoutong
Wu, Yongjun
Yang, Hui
Huang, Yuhui
Hong, Zijian
author_facet Jin, Shoutong
Wu, Yongjun
Yang, Hui
Huang, Yuhui
Hong, Zijian
author_sort Jin, Shoutong
collection PubMed
description Phase-field simulation is a powerful tool for understanding lithium metal electrodeposition. This protocol outlines the process of numerically solving the phase-field equations using the MOOSE framework. Here, we describe steps to obtain the spatiotemporal distribution of major physical characteristics such as phase-field, ion concentration, overpotential, and driving force. Such an approach may help to reveal the underlying physics and kinetics of dendrite growth, while also providing design principles for suppressing lithium dendrites. For complete details on the use and execution of this protocol, please refer to Hong and Viswanathan (2018).
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spelling pubmed-95086042022-09-25 Protocol for phase-field simulations of lithium dendrite growth with MOOSE framework Jin, Shoutong Wu, Yongjun Yang, Hui Huang, Yuhui Hong, Zijian STAR Protoc Protocol Phase-field simulation is a powerful tool for understanding lithium metal electrodeposition. This protocol outlines the process of numerically solving the phase-field equations using the MOOSE framework. Here, we describe steps to obtain the spatiotemporal distribution of major physical characteristics such as phase-field, ion concentration, overpotential, and driving force. Such an approach may help to reveal the underlying physics and kinetics of dendrite growth, while also providing design principles for suppressing lithium dendrites. For complete details on the use and execution of this protocol, please refer to Hong and Viswanathan (2018). Elsevier 2022-09-22 /pmc/articles/PMC9508604/ /pubmed/36149793 http://dx.doi.org/10.1016/j.xpro.2022.101713 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Jin, Shoutong
Wu, Yongjun
Yang, Hui
Huang, Yuhui
Hong, Zijian
Protocol for phase-field simulations of lithium dendrite growth with MOOSE framework
title Protocol for phase-field simulations of lithium dendrite growth with MOOSE framework
title_full Protocol for phase-field simulations of lithium dendrite growth with MOOSE framework
title_fullStr Protocol for phase-field simulations of lithium dendrite growth with MOOSE framework
title_full_unstemmed Protocol for phase-field simulations of lithium dendrite growth with MOOSE framework
title_short Protocol for phase-field simulations of lithium dendrite growth with MOOSE framework
title_sort protocol for phase-field simulations of lithium dendrite growth with moose framework
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9508604/
https://www.ncbi.nlm.nih.gov/pubmed/36149793
http://dx.doi.org/10.1016/j.xpro.2022.101713
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