Optimized synthesis and photovoltaic performance of TiO2 nanoparticles for dye-sensitized solar cell |
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Authors: | Siti Nur Fadhilah Zainudin Masturah Markom Huda Abdullah Renata Adami Siti Masrinda Tasirin |
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Institution: | 1. Department of Chemical Engineering and Process, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia;2. Department of Electrical, Electronic and System Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia;3. Department of Chemical and Food Engineering, University of Salerno, Via Ponte Don Melillo, Fisciano (SA) I-84084, Italy |
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Abstract: | This paper presents response surface methodology (RSM) as an efficient approach for modeling and optimizing TiO2 nanoparticles preparation via co-precipitation for dye-sensitized solar cell (DSSC) performance. Titanium (IV) bis-(acetylacetonate) di-isopropoxide (DIPBAT), isopropanol and water were used as precursor, solvent and co-solvent, respectively. Molar ratio of water, aging temperature and calcination temperature as preparation factors with main and interaction effects on particle characteristics and performances were investigated. Particle characteristics in terms of primary and secondary sizes, crystal orientation and morphology were determined by X-ray diffractometry (XRD) and scanning electron microscopy (SEM). Band gap energy and power conversion efficiency of DSSCs were used for performance studies. According to analysis of variance (ANOVA) in response surface methodology (RSM), all three independent parameters were statistically significant and the final model was accurate. The model predicted maximum power conversion efficiency (0.14%) under the optimal condition of molar ratio of DIPBAT-to-isopropanol-to-water of 1:10:500, aging temperature of 36 °C and calcination temperature of 400 °C. A second set of data was adopted to validate the model at optimal conditions and was found to be 0.14 ± 0.015%, which was very close to the predicted value. This study proves the reliability of the model in identifying the optimal condition for maximum performance. |
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Keywords: | Titanium dioxide Hydrolysis precipitation Dye-sensitized solar cell Optimization Response surface methodology |
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