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In situ XPS confirmed the efficient charge transfer of the CdS/GDY/ZnMoO4 heterojunction based on graphdiyne(CnH2n-2) for photocatalytic hydrogen production

Author

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  • Guo, Xin
  • Fan, Linlin
  • Liu, Yafeng
  • Jin, Zhiliang

Abstract

Graphdiyne (GDY) is a new type of carbon material. Because of its excellent electrical conductivity and adjustable charge distribution, it has attracted wide attention in the field of photocatalysis. In this work, multilayer flake GDY was prepared by ball milling method and CdS/GDY/ZnMoO4 ternary composite catalyst was successfully prepared by physical mixing method. In-situ XPS verified the formation of CdS/GDY/ZnMoO4 heterojunction, which effectively inhibited electron-hole recombination, and also reflected that the new carbon material GDY had strong electron-donating ability. The experimental results show that the CdS/GDY/ZnMoO4 composite catalyst has strong redox activity. Under visible light irradiation, the hydrogen production of CdS/GDY/ZnMoO4 is 1238.61 μmol, which is 16.98 times that of pure CdS. This indicates that GDY can be effectively applied to the field of photocatalytic hydrogen production, providing new possibilities for its application.

Suggested Citation

  • Guo, Xin & Fan, Linlin & Liu, Yafeng & Jin, Zhiliang, 2024. "In situ XPS confirmed the efficient charge transfer of the CdS/GDY/ZnMoO4 heterojunction based on graphdiyne(CnH2n-2) for photocatalytic hydrogen production," Renewable Energy, Elsevier, vol. 222(C).
    • Handle: RePEc:eee:renene:v:222:y:2024:i:c:s0960148123017925
    DOI: 10.1016/j.renene.2023.119877
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    References listed on IDEAS

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    1. Jin, Zhiliang & Jiang, Xudong & Liu, Yanan, 2022. "Graphdiyne(CnH2n-2) based NiS S-scheme heterojunction for efficient photocatalytic hydrogen production," Renewable Energy, Elsevier, vol. 201(P1), pages 854-863.
    2. Dong, Bin & Xie, Jing-Yi & Wang, Nan & Gao, Wen-Kun & Ma, Yu & Chen, Tian-Shu & Yan, Xin-Tong & Li, Qing-Zhong & Zhou, Yu-Lu & Chai, Yong-Ming, 2020. "Zinc ion induced three-dimensional Co9S8 nano-neuron network for efficient hydrogen evolution," Renewable Energy, Elsevier, vol. 157(C), pages 415-423.
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