Cluster Analysis of Combined EDS and EBSD Data to Solve Ambiguous Phase Identifications
Cluster Analysis of Combined EDS and EBSD Data to Solve Ambiguous Phase Identifications
复制标题
结合 EDS 和 EBSD 数据的聚类分析解决模糊相识别问题
DOI：
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发表时间：
2022
影响因子：
2.8
通讯作者：
C. Parish
中科院分区：
文献类型：
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作者：
C. Parish
摘要利用电子背散射衍射（EBSD）技术进行分析扫描电子显微镜（SEM）时，一个常见的问题是具有不同化学性质但晶体结构相同或非常相似的相的分化。x射线能量色散光谱（EDS）有助于区分这些相相似的晶体结构，但不同的元素组成。然而，目前还缺乏基于EDS反应来区分相似EBSD反应阶段的开放、自动化和无偏的方法。本文介绍了一种简单的基于数据分析的方法，利用奇异值分解和聚类分析相结合的方法，将同时获取的EDS + EBSD信息合并，并从它们的晶体和元素数据中自动确定相。我用六角形TiB2陶瓷污染了多个晶体不明确但化学上不同的立方相来说明这种方法。以Python 3 Jupyter Notebook的形式提供的代码以及复制分析所需的必要数据作为补充材料。
Abstract A common problem in analytical scanning electron microscopy (SEM) using electron backscatter diffraction (EBSD) is the differentiation of phases with distinct chemistry but the same or very similar crystal structure. X-ray energy dispersive spectroscopy (EDS) is useful to help differentiate these phases of similar crystal structures but different elemental makeups. However, open, automated, and unbiased methods of differentiating phases of similar EBSD responses based on their EDS response are lacking. This paper describes a simple data analytics-based method, using a combination of singular value decomposition and cluster analysis, to merge simultaneously acquired EDS + EBSD information and automatically determine phases from both their crystal and elemental data. I use hexagonal TiB2 ceramic contaminated with multiple crystallographically ambiguous but chemically distinct cubic phases to illustrate the method. Code, in the form of a Python 3 Jupyter Notebook, and the necessary data to replicate the analysis are provided as Supplementary material.