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

Calendar aging of commercial Li-ion cells of different chemistries – A review

Open access
Dubarry, Matthieu, Qin, Nan, Brooker, Paul·2018·Current Opinion in Electrochemistry

Abstract

Summary In the past twenty years, intensive experimental and modeling efforts have been carried out to access and predict the life expectancy of lithium-ion (Li-ion) batteries under calendar aging conditions. Aging studies are time intensive and usually only focus on one or two chemistries and a few aging conditions. They are therefore not providing a complete understanding of the entire range of temperatures and state of charges. This review is constructed from a comprehensive survey on the Li-ion calendar aging research from the past twenty years. It is the first effort at this scale that provides quantitative and comparative analyses on the aging behaviors of commercially available Li-ion batteries with different cathode and anode chemistries. The results presented in this review can be used to guide future aging studies to fill current knowledge gaps, and can also be used to make an informed selection on Li-ion chemistries for intended applications.

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Crossref · 10.1016/j.coelec.2018.05.023

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Metadata

Authors
Dubarry, M., Qin, N., & Brooker, P.
Venue
Current Opinion in Electrochemistry
Publisher
Elsevier BV
Published
2018-06
Volume
9
Pages
106-113
ISSN
2451-9103 (ISSN-L)
OpenAlex
W2808441473
Cited by
248
References
4
Type
paratext
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Calendar aging of commercial Li-ion cells of different chemistries – A review. https://app.cochat.ai/papers/10.1016/j.coelec.2018.05.023
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Dubarry, M., Qin, N., & Brooker, P. (2018). Calendar aging of commercial Li-ion cells of different chemistries – A review. Current Opinion in Electrochemistry. https://doi.org/10.1016/j.coelec.2018.05.023

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.