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Ultra‐thin Solid‐State Li‐Ion Electrolyte Membrane Facilitated by a Self‐Healing Polymer Matrix
Abstract
Thin solid membranes are formed by a new strategy, whereby an in situ derived self-healing polymer matrix that penetrates the void space of an inorganic solid is created. The concept is applied as a separator in an all-solid-state battery with an FeS2 -based cathode and achieves tremendous performance for over 200 cycles. Processing in dry conditions represents a paradigm shift for incorporating high active-material mass loadings into mixed-matrix membranes.
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Cited by
Bio-based polymers with performance-advantaged properties
Cywar, R. M., Rorrer, N. A., Hoyt, C. B., Beckham, G. T., & Chen, E. Y.-X. (2021) · Nature Reviews Materials · doi:10.1038/s41578-021-00363-3 · Cited by 811
Zhang, Q., Cao, D., Ma, Y., Natan, A., Aurora, P., & Zhu, H. (2019) · Advanced Materials · doi:10.1002/adma.201901131 · Cited by 709
Wang, S., Ma, S., Li, Q., Xu, X., Wang, B., Yuan, W., Zhou, S., You, S., & Zhu, J. (2019) · Green Chemistry · doi:10.1039/c8gc03477j · Cited by 503
Wang, C., Liang, J., Zhao, Y., Zheng, M., Li, X., & Sun, X. (2021) · Energy & Environmental Science · doi:10.1039/d1ee00551k · Cited by 489
Chao, A., Negulescu, I., & Zhang, D. (2016) · Macromolecules · doi:10.1021/acs.macromol.6b01443 · Cited by 417
Metadata
- Authors
- Whiteley, J. M., Taynton, P., Zhang, W., & Lee, S.
- Venue
- Advanced Materials
- Publisher
- Wiley
- Published
- 2015-09-30
- Volume
- 27
- Issue
- 43
- Pages
- 6922-6927
- ISSN
- 0935-9648 (ISSN-L)
- 1521-4095
- OpenAlex
- W2118428226
- Cited by
- 245
- References
- 0
- FWCI
- 5.13
- Type
- journal article
- Language
- en
- Open access
- closed
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- Whiteley, J. M., Taynton, P., Zhang, W., & Lee, S. (2015). Ultra‐thin Solid‐State Li‐Ion Electrolyte Membrane Facilitated by a Self‐Healing Polymer Matrix. Advanced Materials. https://doi.org/10.1002/adma.201502636
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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.
