Quantifying Inhomogeneity of Lithium Ion Battery Electrodes and Its Influence on Electrochemical Performance
This paper presents an approach to quantify microstructural inhomegeneity in lithium ion battery electrodes over multiple length scales and examines the impact of this microstructural inhomogeneity on electrochemical performance. Commerical graphite anodes are investigated because graphite remains t...
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Veröffentlicht in: | Journal of the Electrochemical Society 2018-01, Vol.165 (2), p.A339-A344 |
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Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
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Zusammenfassung: | This paper presents an approach to quantify microstructural inhomegeneity in lithium ion battery electrodes over multiple length scales and examines the impact of this microstructural inhomogeneity on electrochemical performance. Commerical graphite anodes are investigated because graphite remains the anode material of choice due to its low cost, mechanical robustness, and suitable electrochemical properties. At the same time, the graphite anode often plays a role in cell degradation and failure, as lithium plating can occur on the graphite anode during charge, when unfavorable microstructure in the graphite electrode leads to a large overpotential. Here, three-dimensional representations of four different commercial anodes obtained with X-ray tomographic microscopy are statistically analyzed to quantify the microstructural inhomogeneity that is commonly present in lithium ion battery electrodes. Electrochemical simulations on the digitalized microstructures are performed to isolate and understand the influence of different types of microstructural inhomogeneity on battery performance. By understanding how distributions in particle size and shape or slurry and electrode processing cause microstructural inhomogeneity and impact performance, it is possible to determine the extent to which homogeneity should be prioritized for specific applications and how homogeneity could be achieved through smart material selection and processing. |
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ISSN: | 0013-4651 1945-7111 |
DOI: | 10.1149/2.0311802jes |