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Cited by 498

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

Surface-Engineered PtNi-O Nanostructure with Record-High Performance for Electrocatalytic Hydrogen Evolution Reaction

Zhao, Zipeng, Liu, Haotian, Gao, Wenpei, Xue, Wang, Liu, Zeyan, Huang, Jin, Pan, Xiaoqing, Huang, Yu·2018·Journal of the American Chemical Society

Abstract

Hydrogen holds the potential of replacing nonrenewable fossil fuel. Improving the efficiency of hydrogen evolution reaction (HER) is critical for environmental friendly hydrogen generation through electrochemical or photoelectrochemical water splitting. Here we report the surface-engineered PtNi-O nanoparticles with enriched NiO/PtNi interface on surface. Notably, PtNi-O/C showed a mass activity of 7.23 mA/μg at an overpotential of 70 mV, which is 7.9 times higher compared to that of the commercial Pt/C, representing the highest reported mass activity for HER in alkaline conditions. The HER overpotential can be lowered to 39.8 mV at 10 mA/cm 2 when platinum loading was only 5.1 μg pt /cm 2, showing exceptional HER efficiency. Meanwhile, the prepared PtNi-O/C nanostructures demonstrated significantly improved stability as well as high current performance which are well over those of the commercial Pt/C and demonstrated capability of scaled hydrogen generation.

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Cites

Research works printed but not linked: 36

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Metadata

Authors
Zhao, Z., Liu, H., Gao, W., Xue, W., Liu, Z., Huang, J., Pan, X., & Huang, Y.
Venue
Journal of the American Chemical Society
Published
2018-07-07
Volume
140
Issue
29
Pages
9046-9050
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2819625802
Cited by
498
References
15
FWCI
12.72
Type
journal article
Language
en
Open access
closed
Funders
  • Marine Corps Warfighting Laboratory (N000141812155, N000141712608)
  • Division of Chemical, Bioengineering, Environmental, and Transport Systems (CBET 1159240)
  • Division of Materials Research (DMR-1506535, DMR-1420620)

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.