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镧氮共掺杂对钛酸钡光催化电子光学性质的影响:一项密度泛函理论研究

Effects of La-N Co-Doping of BaTiO on Its Electron-Optical Properties for Photocatalysis: A DFT Study.

作者信息

Wang Yang, Zhou Qinyan, Zhang Qiankai, Ren Yuanyang, Cui Kunqi, Cheng Chuanhui, Wu Kai

机构信息

School of Electronics and Information, Xi'an Polytechnic University, Xi'an 710048, China.

Xi'an Key Laboratory of Interconnected Sensing and Intelligent Diagnosis for Electrical Equipment, Xi'an Polytechnic University, Xi'an 710048, China.

出版信息

Molecules. 2024 May 10;29(10):2250. doi: 10.3390/molecules29102250.

Abstract

In cation-anion co-doping, rare earth elements excel at regulating the electronic structure of perovskites, leading to their improved photocatalytic performance. In this regard, the impact of co-doping rare earth elements at the Ba and Ti sites in BaTiO on its electronic and photocatalytic properties was thoroughly investigated based on 2 × 2 × 2 supercell structures of BaTiO with different La concentrations of 12.5% and 25% using DFT calculations. The band structure, density of states, charge density difference, optical properties, and the redox band edge of the co-doped models mentioned above were analyzed. The results indicated that the BaTiO structure co-doped with 25% La at the Ti site exhibited higher absorption in the visible range and displayed a remarkable photocatalytic water-splitting performance. The introduced La dopant at the Ti site effectively reduced the energy required for electronic transitions by introducing intermediate energy levels within the bandgap. Our calculations and findings of this study provide theoretical support and reliable predictions for the exploration of BaTiO perovskites with superior photocatalytic performances.

摘要

在阳离子 - 阴离子共掺杂中,稀土元素擅长调节钙钛矿的电子结构,从而提高其光催化性能。在此方面,基于不同La浓度(12.5%和25%)的BaTiO的2×2×2超晶胞结构,利用密度泛函理论(DFT)计算,深入研究了在BaTiO的Ba和Ti位点共掺杂稀土元素对其电子和光催化性能的影响。分析了上述共掺杂模型的能带结构、态密度、电荷密度差、光学性质以及氧化还原带边。结果表明,在Ti位点共掺杂25% La的BaTiO结构在可见光范围内表现出更高的吸收,并展现出显著的光催化水分解性能。在Ti位点引入的La掺杂剂通过在带隙内引入中间能级有效地降低了电子跃迁所需的能量。本研究的计算和结果为探索具有优异光催化性能的BaTiO钙钛矿提供了理论支持和可靠预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11f9/11123909/4eb3019ee2b0/molecules-29-02250-g001.jpg

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