gene expression programming for green synthesis of silver nanoparticles: size evolution

In this study, gene expression programming (gep) was used as a new method for the formulation of the size of silver nanoparticles (agnps) as functions of the agno3-to-opium syrup (os) ratio, ph, temperature (t), agitation speed (as) and feed rate (fr) of reducing agent in green synthesis. the models differ from each other concerning their genes number, chromosomes, interconnected function, and head size. a total of 63 samples were selected at different practical parameter products to generate databases for the new particle size formulations, testing, and training sets. the training and testing sets included 47 and 16 randomly selected mixtures for the proposed models. the best gep model is found, and this final model can predict the size of agnps with a correlation coefficient (r2) of 0.828, a root means square error (rmse) of 5.894, a root relative squared error (rrse) of 0.44. all results in the models indicated an applicable performance for predicting the minimum particle size of the agnps and found it reliable. the predicted model showed that all of the input parameters affect the resulting particle size. gep modeling results denoted that the selected gep successfully predicts the behavior of the size of nanoparticles as functions of operating variables.