Use of Data-Driven Model to Optimize Scale-up Production of Nanosized Silver Particles

Abstract

Optimization of the synthesis of nanosized silver particles by chemical reduction using formaldehyde in aqueous solution was carried out based on small-scale experimental data (with a 100 cc reaction mixture loaded in a 200 cc beaker and shaken in an isothermal shaker). Effects of the possible processing variables were achieved. In this study, the scale-up production (2 L or more of the reaction mixture) of nanosized silver particles is intended; however, for a scale-up system, the experiments generally require large and expensive resources. To obtain the optimal recipe and operating conditions using limited resources for a scale-up system, an algorithm for extending the identified model built from a small-scale system to a scale-up system was first developed through a numerical example. On the basis of the developed algorithm, 19 experiments were carried out in the scale-up system to achieve the objectives (minimum of the mean particle size of the silver colloid with or without the constraint of conversion of silver nitrate) of the synthesis of nanosized silver particles. With the modeling and optimization method proposed in this work, limited experiments were required, and most of the experiments can produce near on-specification products such that the off-specification products can be minimized.