Citation

Low, Pei Ling and Thien, Gregory Soon How and Eldjilali, Cheikh Zakaria and Sin, Yew Keong and Yeoh, Mian En and Mohd Bakhori, Siti Khadijah and Ab Rahman, Marlinda and Chan, Kah Yoong (2026) Duration and Metal Doping Effects on TiO2 Photoanodes on the Performance of Dye-Sensitized Solar Cells. International Journal of Nanoelectronics and Materials (IJNeaM), 19 (2). pp. 203-212. ISSN 1985-5761

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Abstract

e TiO₂ photoanode is crucial for the photovoltaic performance of dye-sensitized solar cells (DSSCs). Notably, the improved efficiency of TiO₂ photoanodes through metal ion doping significantly depends on changes in their crystal structure, morphology, and optical properties. Therefore, this study explored the drying duration effect of hydrothermally grown TiO₂ colloids (75–120 mins) to optimize the paste for doctor-blading TiO₂ photoanodes. The analysis also investigated the impact of different 1 mol% metal dopants (Sr, Zn, Al, and Nb) on the photoanodes' crystal structure, morphology, optical properties, and DSSC efficiency. Each sample was synthesized using a modified and simplified hydrothermal strategy. The 120-min duration was then determined as the optimal drying duration for producing the highest device efficiency of 3.38% for the pristine TiO₂ photoanode. This enhancement was attributed to improved crystallinity, a more rod-like and porous morphology, and a broader absorption range into visible wavelengths. Among the metal dopants, Nb significantly improved efficiency by 6.5%. In contrast, the other dopants adversely affected performance compared to the pristine TiO₂ photoanode, which was related to the mixed rutile-anatase phase ratio. Consequently, this study effectively optimized TiO2 photoanodes in DSSCs regarding drying duration and metal doping variables based on a simplified hydrothermal approach.

Item Type:	Article
Uncontrolled Keywords:	Solar energy
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK4001-4102 Applications of electric power
Divisions:	Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	04 May 2026 03:31
Last Modified:	04 May 2026 03:31
URII:	http://shdl.mmu.edu.my/id/eprint/15849

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