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Energy‐Saving Electrolytic Hydrogen Generation: Ni2P Nanoarray as a High‐Performance Non‐Noble‐Metal Electrocatalyst

Tang, Chun, Zhang, Rong, Lu, Wenbo, Wang, Zao, Liu, Danni, Hao, Shuai, Du, Gu, Asiri, Abdullah M., Sun, Xuping·2017·Angewandte Chemie International Edition

Abstract

It is highly attractive but challenging to develop earth‐abundant electrocatalysts for energy‐saving electrolytic hydrogen generation. Herein, we report that Ni 2 P nanoarrays grown in situ on nickel foam (Ni 2 P/NF) behave as a durable high‐performance non‐noble‐metal electrocatalyst for hydrazine oxidation reaction (HzOR) in alkaline media. The replacement of the sluggish anodic oxygen evolution reaction with such the more thermodynamically favorable HzOR enables energy‐saving electrochemical hydrogen production with the use of Ni 2 P/NF as a bifunctional catalyst for anodic HzOR and cathodic hydrogen evolution reaction. When operated at room temperature, this two‐electrode electrolytic system drives 500 mA cm−2 at a cell voltage as low as 1.0 V with strong long‐term electrochemical durability and 100 % Faradaic efficiency for hydrogen evolution in 1.0 m KOH aqueous solution with 0.5 m hydrazine.

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Citations

Cites

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Metadata

Authors
Tang, C., Zhang, R., Lu, W., Wang, Z., Liu, D., Hao, S., Du, G., Asiri, A. M., & Sun, X.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2016-12-15
Volume
56
Issue
3
Pages
842-846
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2565244115
Cited by
809
References
9
FWCI
17.52
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Energy‐Saving Electrolytic Hydrogen Generation: Ni2P Nanoarray as a High‐Performance Non‐Noble‐Metal Electrocatalyst. https://app.cochat.ai/papers/10.1002/anie.201608899
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Tang, C., Zhang, R., Lu, W., Wang, Z., Liu, D., Hao, S., Du, G., Asiri, A. M., & Sun, X. (2017). Energy‐Saving Electrolytic Hydrogen Generation: Ni2P Nanoarray as a High‐Performance Non‐Noble‐Metal Electrocatalyst. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201608899

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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.