Comparative study of response surface methodology and artificial neural network for optimization of process parameters for synthesis of gold nanoparticles by extract.

Green synthesis of nanoparticles has gained attention due to its eco-friendly and sustainable approach to synthesize nanoparticles at a reduced cost. Artificial neural network (ANN) and response surface model (RSM) are important to reduce experimental efforts in nanoparticle synthesis. In this work, optimization of gold nanoparticle synthesis by extract was performed using the volume of plant extract, concentration of auric chloride, reaction time, pH, and temperature as process parameters, and the output was absorbance.