Nagatsuma Yuhi, Ohno Munekazu, Takaki Tomohiro, Shibuta Yasushi
Department of Materials Engineering, The University of Tokyo, Tokyo 113-8656, Japan.
Division of Materials Science and Engineering, Faculty of Engineering, Hokkaido University, Sapporo 060-8628, Japan.
Nanomaterials (Basel). 2021 Sep 6;11(9):2308. doi: 10.3390/nano11092308.
Temperature dependence of solid-liquid interfacial properties during crystal growth in nickel was investigated by ensemble Kalman filter (EnKF)-based data assimilation, in which the phase-field simulation was combined with atomic configurations of molecular dynamics (MD) simulation. Negative temperature dependence was found in the solid-liquid interfacial energy, the kinetic coefficient, and their anisotropy parameters from simultaneous estimation of four parameters. On the other hand, it is difficult to obtain a concrete value for the anisotropy parameter of solid-liquid interfacial energy since this factor is less influential for the MD simulation of crystal growth at high undercooling temperatures. The present study is significant in shedding light on the high potential of Bayesian data assimilation as a novel methodology of parameter estimation of practical materials an out of equilibrium condition.
通过基于集合卡尔曼滤波器（EnKF）的数据同化研究了镍晶体生长过程中固液界面性质的温度依赖性，其中相场模拟与分子动力学（MD）模拟的原子构型相结合。通过同时估计四个参数，发现固液界面能、动力学系数及其各向异性参数存在负温度依赖性。另一方面，由于该因素对高过冷温度下晶体生长的MD模拟影响较小，因此难以获得固液界面能各向异性参数的具体值。本研究对于揭示贝叶斯数据同化作为一种在非平衡条件下实际材料参数估计的新方法的巨大潜力具有重要意义。
