JOURNAL ARTICLE

Preparation of Ti3+ Self-Doped TiO2 Material by One Simple Vacuum Heat Treatment and its Simulated Solar Photocatalytic Performance.

  • Published In: Journal of Molecular & Engineering Materials, 2025, v. 13, n. 4. P. 1 1 of 3

  • Database: Applied Science & Technology Source Ultimate 2 of 3

  • Authored By: Lyu, Cui; Liang, Baoyan; Wu, Jingtao 3 of 3

Abstract

Ti 3 + self-doped TiO2 particles were prepared by simple vacuum heat treatment using TiO2 powder and Ti powder as raw materials. The structure, morphology, and elemental presence of the prepared samples were characterized and analyzed using X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and ultraviolet–visible light diffuse reflectance spectroscopy (UV–Vis DRS). The XRD results indicate that Ti doping caused lattice distortion in TiO2. XPS analysis shows that the sample contained Ti 3 + . The DSC result indicates that this Ti 3 + self-doped TiO2 has stronger absorption in the visible light region. Under simulated sunlight irradiation, the prepared samples exhibit significantly better photocatalytic degradation performance than TiO2 raw materials for methylene blue (MB) solution. When the ratio of TiO2 to Ti material was 12:1, the sample achieves the highest catalytic activity, with a degradation rate of MB reaching 99.5% within 45 min. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Molecular & Engineering Materials. 2025/12, Vol. 13, Issue 4, p1
  • Document Type:Article
  • Subject Area:Technology
  • Publication Date:2025
  • ISSN:22512373
  • DOI:10.1142/S2251237325500091
  • Accession Number:186449848
  • Copyright Statement:Copyright of Journal of Molecular & Engineering Materials is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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