Effect of the nature of cationic precursors for SILAR deposition on the performance of CdS and PbS/CdS quantum dot-sensitized solar cells
Source abstract
Abstract
In this work, the influences of cationic precursors on the quality of photoelectrode, consequently on the performance of the quantum dot-sensitized solar cells (QDSCs) have been studied. CdS QDSCs have been prepared using successive ionic layer absorption and reaction (SILAR) method. Three cadmium precursors including nitrate (Cd(NO3)2), chloride (CdCl2), and acetate (Cd(Ac)2) were employed for the synthesis and absorption of CdS nanoparticles on nanostructure TiO2 film. The loading amount and nanoparticle size of the CdS on mesoporous TiO2 film showed a significant difference while using various cadmium precursors in the same SILAR cycles. Both the light-harvesting ability and the obtained incident photon-to-current conversion efficiency values show the trend of deposition rate caused by cadmium precursors. Further, it was proposed that an effective cationic precursor could provide a good connection between QD sensitizer and TiO2 interface by electrochemical impedance spectroscopy analysis. Under AM 1.5 G full one sun illumination, the final power conversion efficiency of CdS QDSC based on Cd(Ac)2 was 2.10 %, and PCE values of 1.57 and 1.20 % were obtained for solar cells sensitized by CdS QDs prepared by CdCl2 and Cd(NO3)2, respectively. The cationic precursor effect was further applied in PbS/CdS co-sensitized solar cells. The PbS/CdS QDSCs based on acetate cationic precursors provide a photocurrent of 19.24 mA/cm2 and PCE of 3.23 % in comparison with 11.26 mA and 2.13 % obtained with nitrate acetate salts. Noticeably, the CdS and PbS/CdS QDSCs based on various cationic precursors prepared by SILAR exhibited good photocurrent stability under several light on–off cycles.
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Research context
OpenAlex topics: TiO2 Photocatalysis and Solar Cells · Advanced Photocatalysis Techniques · Quantum Dots Synthesis And Properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (51)
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