Volume 2 Issue 2
Mar.  2022
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Zheng Caiyan, Zhang Xu, Zhou Zhen, Hu Zhenpeng. A first-principles study on the electrochemical reaction activity of 3d transition metal single-atom catalysts in nitrogen-doped graphene: Trends and hints[J]. eScience, 2022, 2(2): 219-226. doi: 10.1016/j.esci.2022.02.009
Citation: Zheng Caiyan, Zhang Xu, Zhou Zhen, Hu Zhenpeng. A first-principles study on the electrochemical reaction activity of 3d transition metal single-atom catalysts in nitrogen-doped graphene: Trends and hints[J]. eScience, 2022, 2(2): 219-226. doi: 10.1016/j.esci.2022.02.009

A first-principles study on the electrochemical reaction activity of 3d transition metal single-atom catalysts in nitrogen-doped graphene: Trends and hints

doi: 10.1016/j.esci.2022.02.009
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  • Corresponding author: Zhenpeng Hu zphu@nankai.edu.cn
  • Received Date: 2021-12-08
  • Revised Date: 2022-01-01
  • Accepted Date: 2022-02-28
  • Available Online: 2022-03-08
  • Electrochemical reactions are essential in the processes of energy storage and conversion, and performance is tightly dependent on the electrocatalysts. Herein, we systematically investigate the activity of 3d transition metal embedded nitrogen-doped graphene (MNx-G) for single-atom catalysts (SACs) in the oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER). The calculated volcano curves reveal the optimal SAC configuration for each reaction to be CoN3-G for the ORR, CoN4-G for the OER, and Ni/CuN3-G for the HER. Analysis based on the machine learning method suggests that high catalytic performance is dominated by the number of valence electrons occupying the d orbitals, the covalent radius, the electronegativity, the ratio of nearest-neighbor N and C atoms for the metal atoms, and the bond length between metal atoms and adsorbates. This work may shed some light on further studies of the ORR, OER, and HER with non-precious metal SACs.
  • ● Following the basic principle of physics, a comprehensive study on MNx-G based SACs activity is essential to reach an agreement.
    ● Machine learning analysis reveals the factors that affect the catalytic performance.
    ● CoN3-G, CoN4-G and Ni/CuN3-G are predicted to have the optimal ORR, OER and HER activity, respectively.
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