高压物理学报2025，Vol.39Issue(11)：68-84,17.DOI:10.11858/gywlxb.20251141
Al-Cu金属间化合物的机器学习势构建及压缩力学性质
Machine Learning Potential Construction and Compressive Mechanical Properties of Al-Cu Intermetallic Compounds
摘要
Abstract
The optimization design of Al-Cu intermetallic compounds is crucial for the mechanical properties of Al-Cu alloys.Molecular dynamics(MD)simulation can provide microscopic processes of the mechanical behavior of Al-Cu alloys,and the interatomic potential is the key physical basis to ensure the reliability of the MD simulation.This work constructed a depth potential(DP)function for the Al-Cu system based on first-principles calculations,and compared the physical properties predicted by DP(crystal structure,energy-volume curve,pressure-volume curve,and phonon spectrum)with density functional theory(DFT)and embedded atom method(EAM)results.The generalization ability and accuracy of the DP model were verified.Based on the DP potential,MD simulations were conducted on the compression process of five Al-Cu intermetallic compounds(θ-Al2Cu,θ'-Al2Cu,Al3Cu,Al4Cu9,and AlCu4 phases).The characteristics and laws of yielding phenomena in structures such as θ-Al2Cu,θ'-Al2Cu and AlCu4 were presented.The yield stress and shear stress of θ-Al2Cu,θ'-Al2Cu and AlCu4 increase with the increase of strain rate,and the yield strain also increases correspondingly.This phenomenon arises from the enhancement of phonon drag obstruction to atomic slip.Among them,θ-Al2Cu has the best compressive performance,yielding at a strain rate of 4×109 s-1 when compressed to 17.4%,with a yield strength of 51.15 GPa.Screw dislocations are produced,and the atoms slip along the[(1)11],[111]and[11(1)]directions.θ'-Al2Cu yields when compressed to 10.0%,and the atoms slip in the plane perpendicular to the compression.Yielding occurs when the AlCu4 phase is compressed to 13.4%and the atoms slip along the[401]and[40(1)]directions.关键词
Al-Cu合金/机器学习/分子动力学/力学性能/单轴压缩Key words
Al-Cu alloy/machine learning/molecular dynamics/mechanical properties/uniaxial compression分类
金属材料引用本文复制引用
荆琳烁,邵建立,薛峰宁,王裴,徐利春..Al-Cu金属间化合物的机器学习势构建及压缩力学性质[J].高压物理学报,2025,39(11):68-84,17.基金项目
国家重点研发计划(2021YFB3802300) （2021YFB3802300）
