| Molecular dynamics simulation of the transformation of Fe-Co alloy by machine learning force field based on atomic cluster expansion | |
| Li, Yongle1; Xu, Feng1; Hou, Long1; Sun, Luchao2; Su, Haijun3; Li, Xi1,4; Ren, Wei1 | |
| Corresponding Author | Li, Yongle(yongleli@shu.edu.cn) ; Ren, Wei(renwei@shu.edu.cn) |
| 2023-09-01 | |
| Source Publication | CHEMICAL PHYSICS LETTERS
 |
| ISSN | 0009-2614 |
| Volume | 826Pages:6 |
| Abstract | The force field describing the calculated interaction between atoms or molecules is the key to the accuracy of many molecular dynamics (MD) simulation results. Compared with traditional or semi-empirical force fields, machine learning force fields have the advantages of faster speed and higher precision. We have employed the method of atomic cluster expansion (ACE) combined with first-principles density functional theory (DFT) calculations for machine learning, and successfully obtained the force field of the binary Fe-Co alloy. Molecular dynamics simulations of Fe-Co alloy carried out using this ACE force field predicted the correct phase transition range of Fe-Co alloy. |
| Keyword | Molecular dynamics Atomic cluster expansion Fe-Co Alloy Density functional theory Phase transition Force field |
| Funding Organization | National Natural Science Foundation of China ; Science and Technology Commission of Shanghai Municipality ; Key Research Project of Zhejiang Laboratory ; High Performance Computing Center, Shanghai University |
| DOI | 10.1016/j.cplett.2023.140646 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China[52130204] ; National Natural Science Foundation of China[12074241] ; National Natural Science Foundation of China[11929401] ; Science and Technology Commission of Shanghai Municipality[22XD1400900] ; Science and Technology Commission of Shanghai Municipality[20501130600] ; Science and Technology Commission of Shanghai Municipality[20QA1401000] ; Science and Technology Commission of Shanghai Municipality[21JC1402600] ; Science and Technology Commission of Shanghai Municipality[21JC1402700] ; Key Research Project of Zhejiang Laboratory[2021PE0AC02] ; High Performance Computing Center, Shanghai University |
| WOS Research Area | Chemistry ; Physics |
| WOS Subject | Chemistry, Physical ; Physics, Atomic, Molecular & Chemical |
| WOS ID | WOS:001027725000001 |
| Publisher | ELSEVIER |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.imr.ac.cn/handle/321006/178532 |
| Collection | 中国科学院金属研究所 |
| Corresponding Author | Li, Yongle; Ren, Wei |
| Affiliation | 1.Shanghai Univ, Mat Genome Inst, Int Ctr Quantum & Mol Struct, Dept Phys,State Key Lab Adv Special Steels, Shanghai 200444, Peoples R China 2.Chinese Acad Sci, Inst Met Res, Shenyang Natl Lab Mat Sci, Shenyang 110016, Peoples R China 3.Northwestern Polytech Univ, State Key Lab Solidificat Proc, Xian 710072, Peoples R China 4.Shanghai Jiao Tong Univ, Shanghai Key Lab Adv High Temp Mat & Precis Formin, Shanghai 200240, Peoples R China |
| Recommended Citation GB/T 7714 | Li, Yongle,Xu, Feng,Hou, Long,et al. Molecular dynamics simulation of the transformation of Fe-Co alloy by machine learning force field based on atomic cluster expansion[J]. CHEMICAL PHYSICS LETTERS,2023,826:6. |
| APA | Li, Yongle.,Xu, Feng.,Hou, Long.,Sun, Luchao.,Su, Haijun.,...&Ren, Wei.(2023).Molecular dynamics simulation of the transformation of Fe-Co alloy by machine learning force field based on atomic cluster expansion.CHEMICAL PHYSICS LETTERS,826,6. |
| MLA | Li, Yongle,et al."Molecular dynamics simulation of the transformation of Fe-Co alloy by machine learning force field based on atomic cluster expansion".CHEMICAL PHYSICS LETTERS 826(2023):6. |
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