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The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Flexible, solid-state, ion-conducting membrane with 3D garnet nanofiber networks for lithium batteries

Open access
Fu, Kun (Kelvin), Gong, Yunhui, Dai, Jiaqi, Gong, Amy, Han, Xiaogang, Yao, Yonggang, Wang, Chengwei, Wang, Yibo, Chen, Yanan, Yan, Chaoyi, Li, Yiju, Wachsman, Eric D., Hu, Liangbing·2016·Proceedings of the National Academy of Sciences

Abstract

Significance: This work describes a flexible, solid-state, lithium-ion–conducting membrane based on a 3D ion-conducting network and polymer electrolyte for lithium batteries. The 3D ion-conducting network is based on percolative garnet-type Li 6.4 La 3 Zr 2 Al 0.2 O 12 solid-state electrolyte nanofibers, which enhance the ionic conductivity of the solid-state electrolyte membrane at room temperature and improve the mechanical strength of the polymer electrolyte. The membrane has shown superior electrochemical stability to high voltage and high mechanical stability to effectively block lithium dendrites. This work represents a significant breakthrough to enable high performance of lithium batteries.

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Crossref · 10.1073/pnas.1600422113

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Metadata

Authors
Fu, K. (., Gong, Y., Dai, J., Gong, A., Han, X., Yao, Y., Wang, C., Wang, Y., Chen, Y., Yan, C., Li, Y., Wachsman, E. D., & Hu, L.
Venue
Proceedings of the National Academy of Sciences
Published
2016-06-15
Volume
113
Issue
26
Pages
7094-7099
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2436341552
Cited by
930
References
2
FWCI
45.28
Type
journal article
Language
en
Open access
green

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The paper
Fu, K. (., Gong, Y., Dai, J., Gong, A., Han, X., Yao, Y., Wang, C., Wang, Y., Chen, Y., Yan, C., Li, Y., Wachsman, E. D., & Hu, L. (2016). Flexible, solid-state, ion-conducting membrane with 3D garnet nanofiber networks for lithium batteries. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1600422113

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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.