OPTIMIZING DYE-SENSITIZED SOLAR CELL EFFICIENCY THROUGH TiO2/CuS DOPING: EFFECTS OF INTERNAL PARAMETER VARIATIONS

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Abstract

Dye-sensitized solar cells (DSSC) have attracted significant research interest due to their semi-transparency, ease of fabrication, cost-effectiveness, and environmental friendliness. This research focuses on enhancing dye-sensitized solar cells efficiency by doping titanium dioxide with copper sulfide and varying internal parameters such as concentration, thickness, and temperature. The primary issue addressed is the low electron mobility of titanium dioxide, which limits its performance as a photoanode. Using simulation methods, this study analyzed dye-sensitized solar cells performance under different doping conditions. The results showed that the highest efficiency of 8.18 % was achieved at a TiO2/CuS concentration of 0.3 %. The optimal photoanode thickness was approximately 3 μm, yielding an efficiency of 8.33 %. Temperature variations at room temperature (275 K, 300 K, and 325 K) resulted in efficiency values of 13.94 %, 15.06 %, and 16.18 %, respectively. These findings indicate that targeted doping and precise control of internal parameters can significantly enhance the performance of titanium dioxide-based dye-sensitized solar cells. The improved efficiency is attributed to enhanced electron mobility and better structural and morphological characteristics of the doped titanium dioxide photoanode. This research provides valuable insights into developing more efficient and sustainable dye-sensitized solar cells. The practical implications of these results are significant for advancing dye-sensitized solar cells as a viable alternative to conventional solar cells, contributing to the global effort to address the energy crisis by providing a cost-effective and environmentally friendly energy source

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Supriyanto, E., Nawafil, M., & Subekti, A. (2024). OPTIMIZING DYE-SENSITIZED SOLAR CELL EFFICIENCY THROUGH TiO2/CuS DOPING: EFFECTS OF INTERNAL PARAMETER VARIATIONS. Eastern-European Journal of Enterprise Technologies, 4(5(130)), 6–13. https://doi.org/10.15587/1729-4061.2024.310454

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