A Grid search-based response surface methodology for the optimum biosynthesis of silver nanoparticles using Clerodendrum splendens

Abstract

In this paper, we propose a grid search algorithm using response surface methodology (RSM) for optimizing the biosynthesis of silver nanoparticles (AgNPs). A biological method using hot water (HW) Clerodendrum splendens (C. splendens) leaf extract is adopted for the discussion. The RSM integrated central composite design (CCD) is used to derive a quadratic objective function to model the yield of AgNPs by accounting the effects of the processing parameters, namely, C. splendens concentration, pH, and the reaction time. The optimization of the resulting objective function, which is a challenging multi-variate non-convex problem, is solved using a grid search approach. The respective optimum values of the parameters are found to be 54 mL, pH 12, and 23 min and the corresponding AgNPs yield is experimentally verified.