Analysis of structural and functional aging of electrodes in lithium-ion batteries during rapid charge and discharge rates using synchrotron tomography

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 e...

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Bibliographic Details
Published in:Journal of power sources 2019-12, Vol.443, p.227259, Article 227259
Main Authors: Prifling, Benedikt, Ridder, Alexander, Hilger, André, Osenberg, Markus, Manke, Ingo, Birke, Kai Peter, Schmidt, Volker
Format: Article
Language:English
Subjects:
Cyclic aging
Lithium-ion batteries
Particle segmentation
Statistical image analysis
Synchrotron tomography
Trinarization
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Summary: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. •Battery electrodes are cyclically aged and imaged by synchrotron tomography.•A novel data-driven three-phase reconstruction approach is presented.•Single active particles can be distinguished based on the watershed algorithm.•Changes in the electrode morphology are quantified by statistical image analysis.•The structural changes are correlated with the electrochemical performance.
ISSN:0378-7753
1873-2755
DOI:10.1016/j.jpowsour.2019.227259