ANALYSIS OF THE PROCESS OF OBTAINING Sb2(SxSe1-x)3 THIN FILMS FOR SOLAR CELLS
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The fabrication process of Sb2(SxSe1-x)3 thin films plays an important role in determining their physical properties and the efficiency
of solar cells. Studying the interaction of growth condition parameters to optimize the fabrication process and improve the device
efficiency is time-consuming and resource-intensive. In this paper, we analyzed experimental data using machine learning (ML)
methods to optimize the fabrication process of Sb2(SxSe1-x)3 thin films. The optimized ML models demonstrate high accuracy in
predicting the photoconversion efficiency with a root-mean-square error of 1% and a Pearson coefficient of r = 0.9.
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