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Updated: Sep 17, 2025

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组合性社区检测:在原子探头断层扫描数据中自动识别化学分离
Jenna A Bilbrey1, Christina Doty1, Mark G Wirth1
1National Security Directorate, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99352, USA.
概括
我们开发了复合社区检测 (CCD),一种无监督的方法,用于识别原子探头断层扫描数据中的化学模式. 该技术揭示了材料组成和分离,有助于分析先进材料.
科学领域:
- 材料科学 材料科学 材料科学
- 数据科学数据科学数据科学
- 纳米技术 纳米技术
背景情况:
- 原子探测器断层扫描 (APT) 可以生成复杂的3D化学图.
- 分析这些数据集以识别化学动机和分离是具有挑战性的.
- 现有的方法可能需要监督或缺乏解释性.
研究的目的:
- 引入一种完全不受监督的集群方法,即组合社区检测 (CCD).
- 允许在APT数据中识别化学动机和分离模式.
- 为材料表征提供可解释的描述符.
主要方法:
- APT点云被细分为重叠的球形社区.
- 重复的k-means聚类和卢凡社区检测按离子组成将社区组合在一起.
- 科尔莫戈罗夫-斯米尔诺夫统计量化了社区内的离子丰富/耗尽.
主要成果:
- CCD成功地在辐射316不钢中确定了碳化和富含Ni-Si的沉物.
- 一个谷物边界通过Ni和Si缩.
- 空间分析显示,Fe 耗尽在碳化物沉物的侧面.
结论:
- CCD是一种强大的无监督工具,用于分析APT数据中的化学分离.
- 该方法提供了对材料组成和结构的可解释的见解.
- CCD对各种材料和极端环境具有广泛的适用性.
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