同步加速器
电池(电)
电极
锂(药物)
材料科学
锂离子电池
微观结构
电化学
相(物质)
离子
锂电池
断层摄影术
聚类分析
纳米技术
计算机科学
复合材料
人工智能
化学
物理
光学
热力学
物理化学
医学
功率(物理)
有机化学
内分泌学
离子键合
作者
Benedikt Prifling,Alexander Ridder,André Hilger,Markus Osenberg,Ingo Manke,Kai Peter Birke,Volker Schmidt
标识
DOI:10.1016/j.jpowsour.2019.227259
摘要
Predicting and increasing the expected battery lifetime is one of the major objectives in state-of-the-art battery research. Until now, the highly complex mechanisms taking place during cyclic aging are only understood to a certain extent. In the present paper, pristine and cyclically aged battery electrodes are considered and the relationship between their microstructure and functionality is investigated. For this purpose, three-dimensional image data obtained by synchrotron tomography is preprocessed by a novel data-driven trinarization approach based on k-means clustering. This allows us to explicitly distinguish between active material, pore space and the phase consisting of binder and conductive additives. This three-phase reconstruction is completed by a segmentation of active material particles, which enables a comprehensive statistical analysis of the electrode morphology. In addition, the investigation of numerous image characteristics together with electrochemical measurements contributes to a deeper understanding of the underlying aging mechanisms.
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