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Advances and Perspectives of Cathode Storage Chemistry in Aqueous Zinc-Ion Batteries
Abstract
Rechargeable aqueous zinc-ion batteries (AZIBs) have captured a surge of interest in recent years as a promising alternative for scalable energy storage applications owing to the intrinsic safety, affordability, environmental benignity, and impressive electrochemical performance. Despite the facilitated development of this technology by many investigations, however, its smooth implementation is still plagued by inadequate energy density and undesirable life span, which calls for an efficient and controllable cathode storage chemistry. Here, this review focuses on the key bottlenecks by offering a comprehensive summary of representative cathode materials and comparatively analyzing their structural features and electrochemical properties. Then, we critically present several feasible electrode design strategies to guide future research activities from a fundamental perspective for high-energy-density and durable cathode materials mainly in terms of interlayer regulation, defect engineering, multiple redox reactions, activated two-electron reactions, and electrochemical activation and conversion. Finally, we outline the remaining challenges and future perspectives of developing high-performance AZIBs.
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Metadata
- Authors
- Wang, X., Zhang, Z., Xi, B., Chen, W., Jia, Y., Feng, J., & Xiong, S.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2021-06-03
- Volume
- 15
- Issue
- 6
- Pages
- 9244-9272
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W3165021210
- Cited by
- 531
- References
- 120
- FWCI
- 26.07
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Data sources
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.
