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Cited by 235

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

Nanostructure and Advanced Energy Storage: Elaborate Material Designs Lead to High-Rate Pseudocapacitive Ion Storage

Gan, Zihan, Yin, Junyi, Xu, Xin, Cheng, Yonghong, Yu, Ting·2022·ACS Nano

Abstract

The drastic need for development of power and electronic equipment has long been calling for energy storage materials that possess favorable energy and power densities simultaneously, yet neither capacitive nor battery-type materials can meet the aforementioned demand. By contrast, pseudocapacitive materials store ions through redox reactions with charge/discharge rates comparable to those of capacitors, holding the promise of serving as electrode materials in advanced electrochemical energy storage (EES) devices. Therefore, it is of vital importance to enhance pseudocapacitive responses of energy storage materials to obtain excellent energy and power densities at the same time. In this Review, we first present basic concepts and characteristics about pseudocapacitive behaviors for better guidance on material design researches. Second, we discuss several important and effective material design measures for boosting pseudocapacitive responses of materials to improve rate capabilities, which mainly include downsizing, heterostructure engineering, adding atom and vacancy dopants, expanding interlayer distance, exposing active facets, and designing nanosheets. Finally, we outline possible developing trends in the rational design of pseudocapacitive materials and EES devices toward high-performance energy storage.

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Crossref · 10.1021/acsnano.2c00557

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Metadata

Authors
Gan, Z., Yin, J., Xu, X., Cheng, Y., & Yu, T.
Venue
ACS Nano
Published
2022-03-16
Volume
16
Issue
4
Pages
5131-5152
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W4221045566
Cited by
235
References
2
FWCI
9.91
Type
journal article
Language
en
Open access
closed

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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).

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