Lanzhou University of Technology Institutional Repository (LUT_IR)
Deep-learning potential molecular dynamics simulations of the structural and physical properties of rare-earth metal scandium | |
Xue, Hong-Tao1,3![]() ![]() ![]() ![]() ![]() ![]() | |
2024-06 | |
发表期刊 | COMPUTATIONAL MATERIALS SCIENCE
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ISSN | 0927-0256 |
卷号 | 242 |
摘要 | The deep potential (DP) is a promising deep-learning-based approach to developing the high-accurate potential function of various materials from the data of ab-initio calculations based on density functional theory (DFT). To better understand the structural and physical properties of the rare -earth metal scandium (Sc), performing classical molecular dynamics (MD) simulations should be highly beneficial but has been straitened for lacking of available Sc potential. Therefore, the necessary interatomic potential function of Sc for MD simulations was developed first in this work by using the DP method. By systematically comparing the DP-predicted lattice constants, stable phase, vacancy and self-interstitial formation energies, surface energies, elastic constants and generalised stacking fault energy curves with the corresponding DFT results, we validated that the developed DP model of Sc enables these property-predictions with a reasonable DFT accuracy. Moreover, our DP-based MD simulations shown that the rare -earth Sc can transform from the alpha-HCP to the beta-BCC structure at 1622 K and melt at 1710 K, quite close to the experimental values for the alpha- beta phase transition temperature (1609 K) and the melting-point (1814 K) of Sc. Rising temperature can improve the diffusivity of Sc atoms and the self-diffusion coefficient at the melting-point is 5.7 x 10 -12 m 2 /s, which is on the same order of magnitude as other HCP metals. The results could be used for understanding the fundamental properties of rare -earth metal Sc and as a basis for further developing the Sc-containing binary or multinary DP models. |
关键词 | Deep potential Molecular dynamics simulations First-principles calculations Rare-earth metal Sc Phase transformation |
DOI | 10.1016/j.commatsci.2024.113072 |
收录类别 | SCIE ; EI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China [2017YFA0700704]; Guangxi Science and Technology Program [GUI- KEAA22068084]; Chinese Academy of Sciences - Institute of Metal Research [IMR-FWHT-202304-1012]; National Natural Science Foundation of China [12204210]; Major Project of Science and Technology of Gansu Province [22ZD6GA008]; Western Light Talent Culture Project |
WOS研究方向 | Materials Science |
WOS类目 | Materials Science, Multidisciplinary |
WOS记录号 | WOS:001241952100001 |
出版者 | ELSEVIER |
EI入藏号 | 20242016093864 |
EI主题词 | Molecular dynamics |
EI分类号 | 461.4 Ergonomics and Human Factors Engineering ; 547.2 Rare Earth Metals ; 549.3 Nonferrous Metals and Alloys excluding Alkali and Alkaline Earth Metals ; 801.4 Physical Chemistry ; 804.2 Inorganic Compounds ; 922.1 Probability Theory ; 931.2 Physical Properties of Gases, Liquids and Solids ; 931.3 Atomic and Molecular Physics ; 931.4 Quantum Theory ; Quantum Mechanics ; 933.1.1 Crystal Lattice |
原始文献类型 | Article |
EISSN | 1879-0801 |
引用统计 | 无
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文献类型 | 期刊论文 |
条目标识符 | https://ir.lut.edu.cn/handle/2XXMBERH/170732 |
专题 | 省部共建有色金属先进加工与再利用国家重点实验室 材料科学与工程学院 外国语学院 |
通讯作者 | Xue, Hong-Tao; Yang, Yan-Hong |
作者单位 | 1.Lanzhou Univ Technol, Sch Mat Sci & Engn, State Key Lab Adv Proc & Recycling Nonferrous Met, Lanzhou 730050, Peoples R China; 2.Chinese Acad Sci, Inst Met Res, Superalloys Div, 72 Wenhua Rd, Shenyang 110016, Peoples R China; 3.Nanjing Univ Sci & Technol, Herbert Gleiter Inst Nanosci, Sch Mat Sci & Engn, Nanjing 210094, Peoples R China |
第一作者单位 | 材料科学与工程学院 |
通讯作者单位 | 材料科学与工程学院 |
第一作者的第一单位 | 材料科学与工程学院 |
推荐引用方式 GB/T 7714 | Xue, Hong-Tao,Li, Juan,Chang, Zhen,et al. Deep-learning potential molecular dynamics simulations of the structural and physical properties of rare-earth metal scandium[J]. COMPUTATIONAL MATERIALS SCIENCE,2024,242. |
APA | Xue, Hong-Tao.,Li, Juan.,Chang, Zhen.,Yang, Yan-Hong.,Tang, Fu-Ling.,...&Li, Jun-Chen.(2024).Deep-learning potential molecular dynamics simulations of the structural and physical properties of rare-earth metal scandium.COMPUTATIONAL MATERIALS SCIENCE,242. |
MLA | Xue, Hong-Tao,et al."Deep-learning potential molecular dynamics simulations of the structural and physical properties of rare-earth metal scandium".COMPUTATIONAL MATERIALS SCIENCE 242(2024). |
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