扫描电子显微镜
电池(电)
材料科学
锂(药物)
计算机科学
电解质
锂离子电池
聚类分析
能量色散X射线光谱学
主成分分析
电极
过程(计算)
生物系统
人工智能
化学
物理
复合材料
物理化学
内分泌学
功率(物理)
医学
量子力学
操作系统
生物
作者
T. Kato,Kunihiro Goto,Tadao Niwa,Tsukasa Shimizu,Akinobu Fujii,Bunyo Okumura,Hideaki Oka,Hiroaki Kadoura
标识
DOI:10.1038/s41598-025-89362-w
摘要
Abstract The combination of scanning electron microscopy (SEM) images and energy-dispersive X-ray spectroscopy (EDS) maps (SEM–EDS analysis) enables the analysis of the relationship between the microstructures and elemental compositions of the surfaces of materials. However, conventional SEM–EDS analyses lack comprehensiveness and quantitativeness, resulting in potential inaccuracies in reflecting the properties of the entire sample and variations in the results depending on the analyst. Therefore, herein, we propose an objective SEM–EDS analytical process that addresses the aforementioned issues. Comprehensiveness was addressed by acquiring large volumes of SEM images through automated capturing, whereas quantitativeness was addressed through microstructural analysis of the SEM images based on image features, model-based dimension reduction and clustering methods, and similarity analysis of the elemental distribution in EDS maps based on statistical distances. The proposed method was used to analyze the degradation of lithium-ion battery electrodes, affording objective results that align with subjective insights into the changes in the morphology and composition of solid electrolyte interphase (SEI) films accompanying degradation.
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