传输电子显微镜的人工智能辅助工作流程:从数据分析自动化到材料知识揭示
Marc Botifoll1, Ivan Pinto-Huguet1, Enzo Rotunno2
1Catalan Institute of Nanoscience and Nanotechnology - ICN2 (CSIC and BIST), Campus UAB, Bellaterra, Barcelona, 08193, Catalonia, Spain.
Advanced materials (Deerfield Beach, Fla.)
|October 22, 2025
概括
一个新的工作流自动化电子显微镜分析,快速关联原子结构与设备功能. 这种由人工智能驱动的方法为先进材料模拟创建了数字双胞胎,加速了科学发现.
科学领域:
- 材料科学 材料科学 材料科学
- 计算材料科学科学 计算材料科学
- 凝聚物质物理学 凝聚物质物理学
背景情况:
- 扫描传输电子显微镜 ((S) TEM) 对材料科学至关重要,但由于时间限制,它很难将原子结构与设备属性联系起来.
- 描述复杂的设备异构结构需要将晶体学,组成和应变信息与功能行为相关联.
研究的目的:
- 引入一个自动化分析工作流程,用于整体表征,建模和模拟设备异构结构.
- 从几天到几分钟,大大减少 (S) TEM数据分析所需的时间.
- 为了实现数字双胞胎的创建,模拟设备行为和理解结构-属性关系.
主要方法:
- 对 (S) TEM数据进行自动分析,以获得晶体信息,3D定向,元素组成和应变分布.
- 物理引导的人工智能模型对材料和样品描述的应用.
- 对于具有转化不变的系统,生成3D有限元和原子模型 (数字双胞胎).
主要成果:
- 工作流可以在几分钟内自动化复杂的 (S) TEM分析,而此前这项任务需要几天时间.
- 数字双胞胎是为SiGe平面异构结构创建的,可以模拟语音,电子和旋转属性.
- 证明了原子结构和功能性质之间的相关性,包括空间解析特征和自旋轨道长度.
结论:
- 开发的工作流提供了一个快速和全面的方法来表征设备异构结构.
- 由人工智能驱动的数字双胞胎世代为设备行为和材料特性提供了关键的见解.
- 工作流的多功能性在各种材料,设备配置和样本形态学中得到证实.
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