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Cited by 287

The DOI matches its Crossref record; 126 of the 126 references it cites were found in a registry or an index.

Carbon Nitride Materials for Water Splitting Photoelectrochemical Cells

Volokh, Michael, Peng, Guiming, Barrio, Jesús, Shalom, Menny·2019·Angewandte Chemie International Edition

Abstract

Graphitic carbon nitride materials (CNs) have emerged as suitable photocatalysts and heterogeneous catalysts for various reactions thanks to their tunable band gap, suitable energy‐band position, high stability under harsh chemical conditions, and low cost. However, the utilization of CN in photoelectrochemical (PEC) and photoelectronic devices is still at an early stage owing to the difficulties in depositing high‐quality and homogenous CN layer on substrates, its wide band gap, poor charge‐separation efficiency, and low electronic conductivity. In this Minireview, we discuss the synthetic pathways for the preparation of various structures of CN on substrates and their underlying photophysical properties and current photoelectrochemical performance. The main challenges for CN incorporation into PEC cell are described, together with possible routes to overcome the standing limitations toward the integration of CN materials in PEC and other photoelectronic devices.

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Crossref · 10.1002/anie.201806514

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Metadata

Authors
Volokh, M., Peng, G., Barrio, J., & Shalom, M.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2019-02-21
Volume
58
Issue
19
Pages
6138-6151
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2883263021
Cited by
287
References
126
FWCI
7.35
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Carbon Nitride Materials for Water Splitting Photoelectrochemical Cells. https://app.cochat.ai/papers/10.1002/anie.201806514
The paper
Volokh, M., Peng, G., Barrio, J., & Shalom, M. (2019). Carbon Nitride Materials for Water Splitting Photoelectrochemical Cells. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201806514

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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.