No abstract

No abstract

This study presents a new prediction model for estimating the size of silver nanoparticle (AgNPs) prepared by green synthesis via gene expression programming (GEP). Firstly, 30 different experiments were used to construct the GEP models. Plant extract, reaction temperature, concentration of silver nitrate (AgNO 3) and stirring time parameters were considered as input variables and the size of AgNPs parameter selected as output variable. Collected experimentally data randomly divided into 8 testing sets and 22 training sets for further analysis. By consideration of correlation coefficient (R 2), mean absolute error (MAE), root relative square error (RRSE) as criteria, the performance of proposed models by GEP were compared each other. Finally, the best model (i.e., GEP-1) with R 2 =0.9961, MAE=0.2545 and RRSE=0.0668 proposed as a new model with simplified mathematical expressions to estimate the size of AgNPs. The results of sensitivity analysis showed that the amount of plant extract, the concentration of AgNO 3 , stirring time and reaction temperature are the most effective parameters on the size of AgNPs, respectively. Proposed model can be extended for a wide range of applications and provides the possibility of minimum materials consumption for preparation of the lowest size of AgNPs by consideration of practical or economic constraints.