机器学习型分子力场在金属材料相变与变形领域的研究进展

李志尚, 赵龙, 宗洪祥, 丁向东

Machine-Learning Force Fields for Metallic Materials: Phase Transformations and Deformations

LI Zhishang, ZHAO Long, ZONG Hongxiang, DING Xiangdong

图5 MLFFs在传统金属材料准静态加载过程中位错动力学研究中的应用，包括：bcc-Fe的螺位错核心结构，bcc-Fe螺位错的扭结运动模式，1/2<110>螺位错与预先存在位错的Ni/Ni3Al半共格界面相互作用的应力与反应路径的依赖关系，及第一和第二相互作用阶段能量势垒随外部应力的变化[90,91]

Fig.5 Application of MLFFs in dislocation dynamics of conventional metallic materials under quasi-static loading condition (a) screw dislocation core of bcc-Fe (τ—shear stress, a—Peierls valleys spacing, b—Burgers vector modulus)[90] (b) atoms at the dislocation core during a simulation snapshot, evidencing dislocation glide by kink-pair mechanism[90] (c) stress-dependent reaction path of the interaction between an incoming 1/2<110> screw dislocation and the semi-coherent Ni/Ni3Al interface with a preexisting interfacial dislocation[91] (d) variation of energy barrier as a function of the external stress for the first and second interacting stages[91]