Elaboration and characterization of quaternary material Cu2ZnSnS4 by spray pyrolysis technique using Taguchi method
Source abstract
Abstract
In this research work, we used the Taguchi approach to find the optimal condition of parameters to elaborate nanocrystalline of semiconductor Cu2ZnSnS4 (CZTS) using spray pyrolysis technique. To enhance the optical properties (band gap) of CZTS thin films, we used the Taguchi design of experiments with L 27(36) orthogonal array, analysis of variance (ANOVA) and signal-to-noise ratio (S/N). Six deposition parameters called factors, namely deposition temperature, Cu/(Zn + Sn), S/(Cu + Zn + Sn), Zn/Sn ratios, pressure, and deposition time, were selected. For each factor we set three levels by using the Taguchi method to perform the tests. Applying the Taguchi approach, the analysis of the found results showed that the significant factors are the annealing temperature in air and the S/Metal ratio. The influence of deposition parameters on optical, structural, morphological, and electrical properties are studied. CZTS material synthesis with optimal combination of parameters has been characterized, using an UV–visible spectrophotometer (UV–Vis), X-ray diffractometer (XRD), Raman spectroscopy (RM), scanning electron microscopy (SEM), atomic force microscopy (AFM), and four-point probe method. The analysis of optical properties indicated that the energy gap of the CZTS absorbers is 1.52 eV. XRD data showed the formation of pure kesterite structure with a privileged direction along the (112) plan. Raman spectroscopy confirmed the purity of CZTS by observed peaks at 332 and 660 cm−1, SEM micrograph indicated the uniformity of the films and the homogeneity of the grains, atomic force microscopy (AFM) showed the lattice parameters and grain sizes, and the sheet resistance is fixed at 428,4 (ohm/square).
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Research context
OpenAlex topics: Chalcogenide Semiconductor Thin Films · Quantum Dots Synthesis And Properties · Copper-based nanomaterials and applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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