Deep-Learning Potential Molecular Dynamics Study on Nanopolycrystalline Al-Er Alloys: Effects of Er Concentration, Grain Boundary Segregation, and Grain Size on Plastic Deformation.

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Tác giả: Zhen Chang, Li Feng, Jun-Chen Li, Xue-Feng Lu, Jun-Qiang Ren, Fu-Ling Tang, Hong-Tao Xue, Yan-Hong Yang

Ngôn ngữ: eng

Ký hiệu phân loại: 613.2085 Dietetics

Thông tin xuất bản: United States : Journal of chemical information and modeling , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 707324

Understanding the tensile mechanical properties of Al-Er alloys at the atomic scale is essential, and molecular dynamics (MD) simulations offer valuable insights. However, these simulations are constrained by the unavailability of suitable interatomic potentials. In this study, the deep potential (DP) approach, aided by high-throughput first-principles calculations, was utilized to develop an Al-Er interatomic potential specifically for MD simulations. Systematic comparisons between the physical properties (e.g., energy-volume curves, melting point, elastic constants) predicted by the DP model and those obtained from density functional theory (DFT) demonstrated that the developed DP model for Al-Er alloys possesses reliable predictive capabilities while retaining DFT-level accuracy. Our findings confirm that Al
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