Simultaneous Optimization of Nanocrystalline SnO(2) Thin Film Deposition Using Multiple Linear Regressions

A nanocrystalline SnO(2) thin film was synthesized by a chemical bath method. The parameters affecting the energy band gap and surface morphology of the deposited SnO(2) thin film were optimized using a semi-empirical method. Four parameters, including deposition time, pH, bath temperature and tin chloride (SnCl(2)·2H(2)O) concentration were optimized by a factorial method. The factorial used a Taguchi OA (TOA) design method to estimate certain interactions and obtain the actual responses. Statistical evidences in analysis of variance including high F-value (4,112.2 and 20.27), very low P-value (<0.012 and 0.0478), non-significant lack of fit, the determination coefficient (R(2) equal to 0.978 and 0.977) and the adequate precision (170.96 and 12.57) validated the suggested model. The optima of the suggested model were verified in the laboratory and results were quite close to the predicted values, indicating that the model successfully simulated the optimum conditions of SnO(2) thin film synthesis.