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Cited by 624

The DOI matches its Crossref record; 74 of the 74 references it cites were found in a registry or an index.

Multi-electron reaction materials for high energy density batteries

Gao, Xue-Ping, Yang, Han-Xi·2010·Energy Environ. Sci.

Abstract

The need for high energy density batteries becomes increasingly important for the development of new and clean energy technologies, such as electric vehicles and electrical storage from wind and solar power. The search for new energetic materials of primary and secondary batteries with higher energy density has been highlighted in recent years. This review surveys recent advances in the research field of high energy density electrode materials with focus on multi-electron reaction chemistry of light-weight elements and compounds. In the first section, we briefly introduce the basic strategies for enhancement of the energy density of primary batteries based on multi-electron reactions. The following sections present overviews of typical electrode materials with multi-electron chemistry and their secondary battery applications in aqueous and non-aqueous electrolytes. Finally, the challenges and ongoing research strategies of these novel electrode materials and battery systems for high density energy storage and conversion are discussed.

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Metadata

Authors
Gao, X.-P., & Yang, H.-X.
Venue
Energy Environ. Sci.
Published
2010
Volume
3
Issue
2
Pages
174-189
ISSN
  • 1754-5692 (ISSN-L)
  • 1754-5706
OpenAlex
W2093584019
Cited by
624
References
74
FWCI
20.86
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Multi-electron reaction materials for high energy density batteries. https://app.cochat.ai/papers/10.1039/b916098a
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Gao, X.-P., & Yang, H.-X. (2010). Multi-electron reaction materials for high energy density batteries. Energy Environ. Sci. https://doi.org/10.1039/b916098a

Data sources

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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.