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Cited by 420

The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.

Sol Processing of Conjugated Carbon Nitride Powders for Thin‐Film Fabrication

Zhang, Jinshui, Zhang, Mingwen, Lin, Lihua, Wang, Xinchen·2015·Angewandte Chemie International Edition

Abstract

The chemical protonation of graphitic carbon nitride (CN) solids with strong oxidizing acids, for example HNO 3, is demonstrated as an efficient pathway for the sol processing of a stable CN colloidal suspension, which can be translated into thin films by dip/disperse‐coating techniques. The unique features of CN colloids, such as the polymeric matrix and the reversible hydrogen bonding, result in the thin‐film electrodes derived from the sol solution exhibiting a high mechanical stability with improved conductivity for charge transport, and thus show a remarkably enhanced photo‐electrochemical performance. The polymer system can in principle be broadly tuned by hybridization with desired functionalities, thus paving the way for the application of CN for specific tasks, as exemplified here by coupling with carbon nanotubes.

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Crossref · 10.1002/anie.201501001

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Metadata

Authors
Zhang, J., Zhang, M., Lin, L., & Wang, X.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2015-04
Volume
54
Issue
21
Pages
6297-6301
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2139379361
Cited by
420
References
46
FWCI
18.96
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Sol Processing of Conjugated Carbon Nitride Powders for Thin‐Film Fabrication. https://app.cochat.ai/papers/10.1002/anie.201501001
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Zhang, J., Zhang, M., Lin, L., & Wang, X. (2015). Sol Processing of Conjugated Carbon Nitride Powders for Thin‐Film Fabrication. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201501001

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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.