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Opto-electronic properties of hydrothermally grown rod-like TiO2 nanostructures: potential electron transport layer for photovoltaic devices

  • Vivek Dhuliya , Vaibhav Kandwal and L. P. Purohit EMAIL logo
Published/Copyright: August 27, 2025
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Abstract

This study reports the deposition of compact TiO2 (c-TiO2) thin films, which serve as seed layers for the growth of TiO2 nanostructures. Five samples, labeled S1, S2, S3, S4, and S5, were prepared with 2, 4, 6, 8, and 10 deposition cycles of c-TiO2 thin films, respectively. Using the hydrothermal method, rod-like TiO2 nanostructures were successfully grown on these thin films. Field emission scanning electron microscopy images confirmed the formation of rod-like nanostructures with an average length of approximately 0.7 μm, and the number density of the nanorods increased with the seed layer thickness. X-ray diffraction analysis revealed the presence of both anatase and rutile phases of TiO2, with the majority of peaks corresponding to the anatase phase. The UV–Vis transmittance ranged from 60–90 % in the 400–700 nm wavelength range for all five films. The optical band gaps for samples S1, S2, S3, S4, and S5 were 3.11, 3.10, 3.07, 3.05, and 3.05 eV, respectively. Based on the overall characterizations, sample S2 demonstrated the best properties. This study indicates that the TiO2 nanorod layer on the c-TiO2 seed layer effectively enhances the electron transport performance of perovskite-based photovoltaic devices.


Corresponding author: L. P. Purohit, Department of Physics, Gurukula Kangri (Deemed to be University), Haridwar, 249404, Uttarakhand, India, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: Vivek Dhuliya: Data curation, Writing-Original draft preparation, Visualization, Investigation, Software. Vaibhav Kandwal: Characterization, Conceptualization, Investigation. L. P. Purohit: Conceptualization, Methodology, Visualization, Writing-Reviewing and Editing, Supervision.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: V. Dhuliya and L. P. Purohit thank the Uttarakhand State Council for Science and Technology (UCOST), Dehradun, Government of Uttarakhand, for financial support through an R&D Research Project (Project no: UCS&T/R&D-09/21–22/20364/1).

  7. Data availability: The data that support the findings of this study are available from the corresponding author, [L.P.P.], upon reasonable request.

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Received: 2024-01-06
Accepted: 2025-06-29
Published Online: 2025-08-27

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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