| Physics-driven machine learning model on temperature and time-dependent deformation in lithium metal and its finite element implementation | |
Wen JC(温济慈) ; Zou, Qingrong1; Wei YJ(魏宇杰)
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| Source Publication | JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS
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| 2021-08 | |
| Volume | 153Pages:104481 |
| ISSN | 0022-5096 |
| Abstract | Precise understanding on the temperature and time-dependent deformation in lithium-metal anode is of compelling need for durable service of Li-based batteries. Due to both temporal and spatial intertwined thermal agitations and the scarcity of experiments, faithful deformation map of Li-metal covering a broad range of service condition is still lacking. Here we design a physicsdriven machine learning (PD-ML) algorithm to map the temperature, stress and rate-dependent deformation in Li-metal. We demonstrate that the PD-ML model, fed with limited experimental results, can predict the mechanical response of Li-metal in a wide span of temperature and deformation rate, and help to realize a deformation map of Li-metal with high fidelity. A finite element (FE) procedure based on the PD-ML constitutive model is then developed. The integration of PD-ML with FE procedure inherits the power of FE analysis and the accuracy originated from PD-ML in describing temperature, stress and rate-dependent mechanical response of Limetal. The method introduced here paves a new way for constitutive modelling to capture the complex deformation in solids involving multi-field and multiscale mechanics. |
| Keyword | Physics-driven machine learning Lithium-metal anode Creep Finite-element analysis Constitutive model |
| Subject Area | Materials Science, Multidisciplinary ; Mechanics ; Physics, Condensed Matter |
| DOI | 10.1016/j.jmps.2021.104481 |
| Indexed By | SCI ; EI |
| Language | 英语 |
| WOS ID | WOS:000663803400004 |
| Funding Organization | NSFC Basic Science Center for 'Multiscale Problems in Nonlinear Mechanics' [11988102] ; National Natural Science Foundation of China (NSFC) [12002343] ; Strategic Priority Research Program of the Chinese Academy of Sciences [XDB22020200] ; CAS Center for Excellence in Complex System Mechanics ; Scientific Research Foundation Project of Beijing Information Science and Technology University [2025032] |
| Classification | 一类/力学重要期刊 |
| Ranking | 1 |
| Contributor | Wei, YJ (corresponding author), Chinese Acad Sci, Inst Mech, State Key Lab Nonlinear Mech LNM, Beijing 100190, Peoples R China. ; Wei, YJ (corresponding author), Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China. |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://dspace.imech.ac.cn/handle/311007/90258 |
| Collection | 非线性力学国家重点实验室 |
| Affiliation | 1.Chinese Acad Sci, Inst Mech, State Key Lab Nonlinear Mech LNM, Beijing 100190, Peoples R China 2.Beijing Informat Sci & Technol Univ, Sch Appl Sci, Beijing 100192, Peoples R China 3.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China |
| Recommended Citation GB/T 7714 | Wen JC,Zou, Qingrong,Wei YJ. Physics-driven machine learning model on temperature and time-dependent deformation in lithium metal and its finite element implementation[J]. JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS,2021,153:104481.Rp_Au:Wei, YJ (corresponding author), Chinese Acad Sci, Inst Mech, State Key Lab Nonlinear Mech LNM, Beijing 100190, Peoples R China., Wei, YJ (corresponding author), Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China. |
| APA | 温济慈,Zou, Qingrong,&魏宇杰.(2021).Physics-driven machine learning model on temperature and time-dependent deformation in lithium metal and its finite element implementation.JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS,153,104481. |
| MLA | 温济慈,et al."Physics-driven machine learning model on temperature and time-dependent deformation in lithium metal and its finite element implementation".JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS 153(2021):104481. |
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| Physics-driven machi（3559KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Download | |
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