Molecular dynamics simulations of the shear and tensile mechanical properties of rare-earth metal erbium based on deep-learning potential

doi:10.1016/j.mtcomm.2024.110485

IMR OpenIR

	Molecular dynamics simulations of the shear and tensile mechanical properties of rare-earth metal erbium based on deep-learning potential
	Xue, Hong-Tao 1,3; Chang, Zhen 1; Li, Juan 1; Yang, Yan-Hong 2; Ren, Jun-Qiang 1; Zhang, Yong 3; Tang, Fu-Ling 1; Lu, Xue-Feng 1; Li, Jun-Chen 1
通讯作者	Xue, Hong-Tao(xueht@lut.edu.cn) ; Yang, Yan-Hong(yhyang@imr.ac.cn)
	2024-12-01
发表期刊	MATERIALS TODAY COMMUNICATIONS
卷号	41 页码:11
摘要	To gain atomic insights into the physical and mechanical properties of rare-earth metal erbium (Er), performing molecular dynamics (MD) simulations is highly advantageous but has been constrained for lacking of Er interatomic potential. In this work, the essential Er potential for MD simulations was developed by using the deep-potential (DP) method based on first-principles calculations. By systematically comparing the DP-predicated physical properties (melting and solidifying points, elastic properties, etc.) with the results of density functional theory (DFT), experimental or MEAM, we demonstrated that the developed DP model of Er exhibits satisfactory generalization ability and reasonable DFT accuracy on predicting these properties. From the DP-predicted results, we confirmed that the HCP-Er is mechanically stable. The melting point of HCP-Er is 1847 K, while the solidifying point is 1105 K at the cooling rate of 1x10(11) K/s. Moreover, we found that the prismatic unstable stacking fault energy of HCP-Er is lower than the basal one, indicating that the Shockley partial dislocation along prismatic planes is easier to slip. The basal/prismatic and prismatic/basal interfaces were discovered during the tensile deformation of HCP-Er single-crystal along the [0001] direction, signifying the occurrence of the parent-to-'twin' lattice reorientation. The yield strength of HCP-Er decreases from 5.41 to 5.21 GPa with rising the temperature from 150 to 500 K. The results would be helpful for better understanding the mechanical behaviors of metal Er and further developing the binary or multinary Er-containing DP models.
关键词	Deep-learning potential Molecular dynamic simulations First-principles calculations Rare-earth erbium Basal/prismatic interfaces Shear and tensile deformations
资助者	Major Project of Science and Technology of Gansu Province ; Guangxi Science and Technology Program ; Chinese Academy of Sciences-Institute of Metal Research ; Joint Research Fund Project of Gansu Province ; National Natural Science Foundation of China ; Western Light Talent Culture Project
DOI	10.1016/j.mtcomm.2024.110485
收录类别	SCI
语种	英语
资助项目	Major Project of Science and Technology of Gansu Province[22ZD6GA008] ; Guangxi Science and Technology Program[GUIKEAA22068084] ; Chinese Academy of Sciences-Institute of Metal Research[IMR-FWHT-202304-1012] ; Joint Research Fund Project of Gansu Province[24JRRA1104] ; National Natural Science Foundation of China[12204210] ; Western Light Talent Culture Project
WOS研究方向	Materials Science
WOS类目	Materials Science, Multidisciplinary
WOS记录号	WOS:001321922600001
出版者	ELSEVIER
引用统计	被引频次：3[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/190358
专题	中国科学院金属研究所
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
推荐引用方式 GB/T 7714	Xue, Hong-Tao,Chang, Zhen,Li, Juan,et al. Molecular dynamics simulations of the shear and tensile mechanical properties of rare-earth metal erbium based on deep-learning potential[J]. MATERIALS TODAY COMMUNICATIONS,2024,41:11.
APA	Xue, Hong-Tao.,Chang, Zhen.,Li, Juan.,Yang, Yan-Hong.,Ren, Jun-Qiang.,...&Li, Jun-Chen.(2024).Molecular dynamics simulations of the shear and tensile mechanical properties of rare-earth metal erbium based on deep-learning potential.MATERIALS TODAY COMMUNICATIONS,41,11.
MLA	Xue, Hong-Tao,et al."Molecular dynamics simulations of the shear and tensile mechanical properties of rare-earth metal erbium based on deep-learning potential".MATERIALS TODAY COMMUNICATIONS 41(2024):11.