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Cited by 239

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Designing Hierarchically Nanostructured Conductive Polymer Gels for Electrochemical Energy Storage and Conversion

Open access
Shi, Ye, Yu, Guihua·2016·Chemistry of Materials

Abstract

Abstract Nanostructured conductive polymers have been widely researched for various applications such as energy storage and conversion, chemical/biological sensors, and biomedical devices. Recently, novel synthetic methods which adopt doping molecules as cross-linker have been developed to prepare conductive polymer gels (CPGs) with cross-linked network and 3D hierarchically porous nanostructures. The CPGs, as well as their derived carbon frameworks, exhibit high electrical conductivity, large surface area, structural tunability, and hierarchical porosity for rapid mass/charge transport, which contribute to their high performance when applied for energy storage and conversion devices. This Perspective highlights the key features of CPGs and their derived carbon frameworks, discusses their possibilities in terms of rational synthesis and energy-related applications, and proposes future directions for their technological development.

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Crossref · 10.1021/acs.chemmater.5b04879

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Metadata

Authors
Shi, Y., & Yu, G.
Venue
Chemistry of Materials
Published
2016-02-29
Volume
28
Issue
8
Pages
2466-2477
ISSN
  • 0897-4756 (ISSN-L)
  • 1520-5002
OpenAlex
W2291170920
Cited by
239
References
4
FWCI
29.69
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Designing Hierarchically Nanostructured Conductive Polymer Gels for Electrochemical Energy Storage and Conversion. https://app.cochat.ai/papers/10.1021/acs.chemmater.5b04879
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Shi, Y., & Yu, G. (2016). Designing Hierarchically Nanostructured Conductive Polymer Gels for Electrochemical Energy Storage and Conversion. Chemistry of Materials. https://doi.org/10.1021/acs.chemmater.5b04879

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.