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Cited by 237

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Theoretical Analysis of Stresses in a Lithium Ion Cell

Open access
Renganathan, Sindhuja, Sikha, Godfrey, Santhanagopalan, Shriram, White, Ralph E.·2010·Journal of The Electrochemical Society

Abstract

A mathematical model to simulate the generation of mechanical stress during the discharge process in a dual porous insertion electrode cell sandwich comprised of lithium cobalt oxide and carbon is presented. The model attributes stress buildup within intercalation electrodes to two different aspects: changes in the lattice volume due to intercalation and phase transformation during the charge/discharge process. The model is used to predict the influence of cell design parameters such as thickness, porosity, and particle size of the electrodes on the magnitude of stress generation. The model developed in this study can be used to understand the mechanical degradation in a porous electrode during an intercalation/deintercalation process, and the use of this model results in an improved design for battery electrodes that are mechanically durable over an extended period of operation.

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Metadata

Authors
Renganathan, S., Sikha, G., Santhanagopalan, S., & White, R. E.
Venue
Journal of The Electrochemical Society
Published
2010
Volume
157
Issue
2
Pages
A155
ISSN
0013-4651 (ISSN-L)
OpenAlex
W2088491799
Cited by
237
References
4
FWCI
10.82
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Theoretical Analysis of Stresses in a Lithium Ion Cell. https://app.cochat.ai/papers/10.1149/1.3261809
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Renganathan, S., Sikha, G., Santhanagopalan, S., & White, R. E. (2010). Theoretical Analysis of Stresses in a Lithium Ion Cell. Journal of The Electrochemical Society. https://doi.org/10.1149/1.3261809

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.