直接模拟和机器学习结构识别解软 martensitic 转换和结对动态
Jun-Ichi Fukuda1,2, Kazuaki Z Takahashi3
1Department of Physics, Faculty of Science, Kyushu University, Nishi-ku, Fukuoka 819-0395, Japan.
概括
研究人员模拟了液晶蓝色相 (BP) 中的马石转化. 机器学习显示,缺陷结断裂驱动了从BP II到双胞胎BP I的过渡,这与温度是可逆的.
科学领域:
- 材料科学 材料科学 材料科学
- 统计物理 统计物理
- 软物质物理学 软物质物理学
背景情况:
- 马石转换涉及无扩散相变,在材料科学和统计物理学中至关重要.
- 这种现象通常在晶体固体中观察到,但在软材料中越来越多地观察到,由于复杂的分子结构而带来挑战.
研究的目的:
- 直接模拟和研究液晶蓝色相 (BP) 中的中层结构转变.
- 使用先进的计算方法,解开软物质中马氏体变化的动态过程.
主要方法:
- 模拟了蓝色阶段II (BP II) 的介质层结构过渡,使用Langevin类型方程用于带有热波动的方向顺序参数.
- 使用机器学习辅助分析来识别和跟踪阶段过渡期间的局部结构变化.
主要成果:
- 成功模拟了从BP II的完美格子转变为蓝色阶段I (BP I) 的双胞胎格子.
- 鉴定了BP I的核化,其始发于分离线缺陷连接点的断裂,随后是网络变形.
- 通过温度变化证明了双胞胎BP I和BP II之间的可逆转换.
结论:
- 机器学习驱动的模拟提供了前所未有的洞察力,了解软材料中马氏体转化动态.
- 这项研究阐明了拓缺陷在复杂有序系统中的驱动阶段过渡中的作用.
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