Inverted Bilayered Opal Photoanodes for Dye Sensitised Solar Cells

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Page Numbers: 345-354
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Published: Aug 3, 2026
Digital Object Identifier: 10.58578/amjsai.v3i3.11642
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Authors:
E. A. Kamba1*, E. A. Yerima2, E. B. AttahDaniel3
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E. A. Kamba
Federal University Wukari, Taraba State, Nigeria
E. A. Yerima
Federal University Wukari, Taraba State, Nigeria
E. B. AttahDaniel
Federal University Wukari, Taraba State, Nigeria

Abstract

Developing efficient photoanode materials remains a major challenge in improving the performance of dye-sensitized solar cells (DSSCs). This study aims to fabricate and evaluate a bilayer photoanode comprising potassium titanate (K₂Ti₄O₉) nanobelts coupled with a zinc oxide (ZnO) inverse-opal structure and to investigate the effects of electrolyte cation identity and concentration on DSSC performance. K₂Ti₄O₉ nanobelts were synthesized through a solid-state reaction between potassium carbonate (K₂CO₃) and titanium dioxide (TiO₂) and subsequently integrated with the ZnO inverse-opal layer. Photocurrent–voltage measurements were conducted using a two-electrode DSSC configuration containing an I₃⁻/I⁻ redox electrolyte. The devices were illuminated using a 300 W xenon arc lamp equipped with an AM 1.5G filter at an intensity of 100 mW cm⁻². The findings show that the ZnO inverse-opal/K₂Ti₄O₉ bilayer system achieved a photoelectric conversion efficiency of 1.19%, exceeding the 1.04% efficiency obtained using the single K₂Ti₄O₉ system. This improvement indicates that the ZnO inverse-opal layer contributes substantially to device performance by functioning as a photonic-crystal underlayer. The study demonstrates the potential of integrating ZnO inverse-opal structures with K₂Ti₄O₉ nanobelts to enhance DSSC photoanode performance and provides a basis for developing bilayered photonic architectures for solar-energy conversion.

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How to Cite
Kamba, E. A., Yerima, E. A., & AttahDaniel, E. B. (2026). Inverted Bilayered Opal Photoanodes for Dye Sensitised Solar Cells. African Multidisciplinary Journal of Sciences and Artificial Intelligence, 3(3), 345-354. https://doi.org/10.58578/amjsai.v3i3.11642

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