Chinese Journal of Catalysis ›› 2024, Vol. 63: 244-257.DOI: 10.1016/S1872-2067(24)60084-7

• Articles • Previous Articles     Next Articles

Single-atom catalysts based on polarization switching of ferroelectric In2Se3 for N2 reduction

Nan Mua, Tingting Boa, Yugao Hua, Ruixin Xua, Yanyu Liub,*(), Wei Zhoua,*()   

  1. aDepartment of Physics, Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology, School of Science, Tianjin University, Tianjin 300072, China
    bCollege of Physics and Materials Science, Tianjin Normal University, Tianjin 300387, China
  • Received:2024-05-07 Accepted:2024-06-24 Online:2024-08-18 Published:2024-08-19
  • Contact: *E-mail: yyliu@tjnu.edu.cn (Y. Liu), weizhou@tju.edu.cn (W. Zhou).
  • Supported by:
    National Natural Science Foundation of China(51972227);Arts and Science Excellence and Innovation Award Program for Graduate Student of Tianjin University(B2-2023-005)

Abstract:

The polarization switching plays a crucial role in controlling the final products in the catalytic process. The effect of polarization orientation on nitrogen reduction was investigated by anchoring transition metal atoms to form active centers on ferroelectric material In2Se3. During the polarization switching process, the difference in surface electrostatic potential leads to a redistribution of electronic states. This affects the interaction strength between the adsorbed small molecules and the catalyst substrate, thereby altering the reaction barrier. In addition, the surface states must be considered to prevent the adsorption of other small molecules (such as *O, *OH, and *H). Furthermore, the V@↓-In2Se3 possesses excellent catalytic properties, high electrochemical and thermodynamic stability, which facilitates the catalytic process. Machine learning also helps us further explore the underlying mechanisms. The systematic investigation provides novel insights into the design and application of two-dimensional switchable ferroelectric catalysts for various chemical processes.

Key words: In2Se3 monolayer, Density functional theory, Ferroelectric switching, Single atom catalysts, Nitrogen reduction reaction, Machine learning