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The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Unlocking the Potential of Cation-Disordered Oxides for Rechargeable Lithium Batteries

Lee, Jinhyuk, Urban, Alexander, Li, Xin, Su, Dong, Hautier, Geoffroy, Ceder, Gerbrand·2014·Science

Abstract

Disorderly Flow: Lithium batteries are becoming ever more important in society. While their application used to be confined to portable electronics, they are now becoming the enabling technology for electric vehicles and grid storage for renewables. Generally, the flow of lithium ions into and out of battery electrodes is thought to require ordered materials. Lee et al. (p. 519 , published online 9 January) used a combination of experimental work and computations to identify disordered electrode materials with high Li diffusion. The improved energy density properties could be attributed to compositions with excess lithium beyond the stoichiometric limit, leading to intermixing between the lithium and transition metal sublattices and the formation of a percolation network providing specific lithium transport pathways.

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Crossref · 10.1126/science.1246432

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Metadata

Authors
Lee, J., Urban, A., Li, X., Su, D., Hautier, G., & Ceder, G.
Venue
Science
Published
2014-01-31
Volume
343
Issue
6170
Pages
519-522
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2071355028
Cited by
1,248
References
5
FWCI
48.29
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Unlocking the Potential of Cation-Disordered Oxides for Rechargeable Lithium Batteries. https://app.cochat.ai/papers/10.1126/science.1246432
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Lee, J., Urban, A., Li, X., Su, D., Hautier, G., & Ceder, G. (2014). Unlocking the Potential of Cation-Disordered Oxides for Rechargeable Lithium Batteries. Science. https://doi.org/10.1126/science.1246432

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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.