Deposition, characterizations and photoelectrochemical performance of nanocrystalline Cu-In-Cd-S-Se thin films by hybrid chemical process

作者:Khot Kishorkumar V*; Dongale Tukaram D; Mali Sawanta S; Hong Chang Kook; Kamat Rajanish K; Bhosale Popatrao N*
来源:Journal of Materials Science, 2017, 52(16): 9709-9727.
DOI:10.1007/s10853-017-1124-4

摘要

Nanocrystalline, uniform, pentanary mixed metal chalcogenide (PMMC) thin films of copper indium cadmium sulfoselenide (CuInCd(SSe)(3)) were successfully synthesized using simple, self-organized, arrested precipitation technique in an aqueous alkaline medium. The optical, structural, morphological, compositional and electrical properties of synthesized thin films were investigated as a function indium (In3+) concentration. An optical absorption study revealed that direct allowed transition and band gap energy decreases typically from 1.46 to 1.25 eV. The X-ray diffraction studies revealed that the PMMC thin films have a nanocrystalline nature and crystallite size increases with the increase in the In3+ concentration. Tuning of surface morphology from nanospheres to peas-like morphology with uniform, well-adhered distributed throughout the substrate surface were observed by field emission scanning electron microscopy micrographs. The high-resolution transmission electron microscopy images and selected area electron diffraction pattern were illustrated that compactly interconnected particles with nanocrystalline nature. Energy-dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy results confirmed that synthesized thin films had an appropriate chemical purity. The electrical conductivity and thermoelectric power measurement indicates that, the films have n-type conductivity. A photoelectrochemical conversion efficiency of 2.40% was achieved with a current density of 2.87 mA/cm(2). The developed route may provide an alternative approach to synthesize multinary metal chalcogenide thin-film solar cell. Furthermore, we have developed a predictive model of a CICSSe thin-film solar cell using the artificial neural network. The proposed model is useful for the integrated development environment for the predictive modeling and design of high-efficient solar cells.

  • 出版日期2017-8