J. Mater. Sci. Technol. ›› 2022, Vol. 122: 84-90.DOI: 10.1016/j.jmst.2021.12.062

• Research Article • Previous Articles     Next Articles

Accurate structural descriptor enabled screening for nitrogen and oxygen vacancy codoped TiO2 with a large bandgap narrowing

Kangyu Zhanga,b, Lichang Yina,b,c,*(), Gang Liua,b,*(), Hui-Ming Chenga   

  1. aShenyang National Laboratory for Materials Science, Institute of Metal Research, Chinese Academy of Sciences, Shenyang 110016, China
    bSchool of Materials Science and Engineering, University of Science and Technology of China, Shenyang 110016, China
    cDepartment of Physics and Electronic Information, Huaibei Normal University, Huaibei 235000, China
  • Received:2021-11-10 Revised:2021-12-19 Accepted:2021-12-21 Published:2022-09-20 Online:2022-03-20
  • Contact: Lichang Yin,Gang Liu
  • About author:gangliu@imr.ac.cn (G. Liu).
    * Shenyang National Laboratory for Materials Science, Institute of Metal Research, Chinese Academy of Sciences, Shenyang 110016, China. E-mail addresses: lcyin@imr.ac.cn (L. Yin),

Abstract:

Nitrogen (N) doping has been widely adopted to improve the light absorption of TiO2. However, the newly introduced N-2p states are largely localized thus barely overlap with O-2p states in the valence band of TiO2, resulting in a shoulder-like absorption edge. To realize an apparent overlap between N-2p and O-2p states, charge compensation between N3- and O2- via electron transfer from oxygen vacancies (VO) to N dopants is one possible strategy. To verify this, in numerous doping configurations of N/VO-codoped anatase TiO2, we identified two types of VO position independent N-dopant spatial orderings by efficient screening enabled with a newly designed structural descriptor. Compared with others, these two types of the N-dopant spatial orderings are highly beneficial for charge compensation to produce an apparent overlap between N-2p and O-2p states, therefore achieving a large bandgap narrowing. Furthermore, the two types of the N-dopant spatial orderings can also be generalized to N/VO-codoped rutile TiO2 for bandgap narrowing.

Key words: Structural descriptor, TiO2, Bandgap narrowing, Doping, Machine learning, Density functional theory