SIZE PREDICTION OF SILVER NANOPARTICLES USING ARTIFICIAL NEURAL NETWORK

Abstract

The study emphasized the estimation and prediction of the size of silver nanoparticles, which are prepared via green synthesis, using the concept of an artificial neural network. A certain number of recordings of a suitable, thoroughly conducted experiment was taken into account, in which parameters like concentration of plant extract, reaction temperature, the concentration of silver nitrate and stirring duration were taken as input, whereas the size of silver nanoparticles was taken as the undisputed output. After taking all the possible parameters into account, we have been able to design an artificial neural network controller using the MATLAB platform, based completely on back propagation algorithm. After rigorous training of the ANN controller and adjusting the relevant network-based controller parameters, it is found to be performing close enough to expect. And as a result, we have also been able to determine the contribution of each factor involved in tuning the size of silver nanoparticles formed or prepared. We believe this proposed model can contribute to a greater extent when it comes to exploration of a wide range of applications and to exploration of possibilities of reduction of requirement of materials to a huge extent to produce silver nanoparticles with desirable sizes under optimised condition.