Optimization of the Green Synthesis of Tin Oxide nanoparticles bu Response Surface Methodology Using Box-Behnken Design

Abstract

In this paper, tin oxide nanoparticles (Nps) was synthesize via green route using SnCl2.2H20 and Euphorbia trigona (African cactus) plant extract as precursors. Process parameters such as solution pH, precursor concentration and synthesis temperature were optimized to produce Nps with smaller size. The level of sensitivity of the synthesis parameters towards response and the optimization was carried out by applying the Box-Behnken Design from Response Surface Methodology (RSM). The Box-Behnken Design was selected as a statistical prediction method with the aim of reducing the number of experimental runs, which would invariably save time and chemicals, thereby reducing the overall cost of production. The size of the nanoparticles was selected as the response factor for the green synthesis. The optimum predicted conditions obtained for Sn02 were at a solution pH of 10, precursor concentration of 0.40 M and synthesis temperature of 57.5°C. The particle size from the optimized experimental conditions was found to be 6.71 nm, which was also found to be in good agreement with predicted value of 6.73 nm from the developed models. These result was justified by the relatively high correlation coefficients of SnO2 Nps (R2= 99.96, Ridj =99.87, R2pred =99.28) obtained from the statistical prediction after the Analysis of Variance (ANOVA).