Deep-learning potential molecular dynamics simulations of the structural and physical properties of rare-earth metal scandium

doi:10.1016/j.commatsci.2024.113072

	Deep-learning potential molecular dynamics simulations of the structural and physical properties of rare-earth metal scandium
	Xue, Hong-Tao1,3 ; Li, Juan1 ; Chang, Zhen 1; Yang, Yan-Hong 2; Tang, Fu-Ling1 ; Zhang, Yong 3; Ren, Jun-Qiang1 ; Lu, Xue-Feng1 ; Li, Jun-Chen1
	2024-06
发表期刊	COMPUTATIONAL MATERIALS SCIENCE
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
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).