Optimization of the Green Synthesis of Tin Oxide Nanoparticles by Response Surface Methodology (RSM) using Box-Behnken Design

Abstract

Tin oxide nanoparticles has been synthesized via green route using SnCl.2HO and Euphorbia trigona (African 2 2cactus) plant extract as precursors. In this green route process parameters such as, solution pH, precursor concentration and synthesis temperature were optimized to produce nanoparticles with smaller size. The degree of sensitivity of the process parameters vis-a-viz towards optimization were carried out by applying the Box-Behnken Design from Response Surface Methodology (RSM). The Box-Behnken Design was designated as a statistical prediction technique with the goal of decreasing the number of possible experimental outcomes, which would invariably reduced time and quantity of reagents, by this means plummeting the general cost of the production process. The particle size of the nanoparticles was chosen as the response factor for the green synthesis. The optimal predicted conditions obtained tetragonal cassiterite phase of SnO were at a solution pH of 10, precursor concentration of 0.40 M and synthesis 2 οtemperature of 57.5C. From the optimized experimental conditions, the particle size was found to be 6.71 nmwhich , was also found to be in accordance with predicted value of 6.73 nm from the developed model. These results were 2 2 2substantiated by the comparatively high correlation coefficients of SnO NPs (R= 99.96, R = 99.87, R =99.28) 2 adj predobtained from the statistical prediction after the Analysis of Variance (ANOVA).