Modeling Linear Ooptical Properties of Hydrothermally Synthesized ZnO Nanoparticles with Artificial Neural Network (ANN)

In the present work, the influences of synthetic parameters on the optical properties of hydrothermally synthesized ZnO nanoparticles were investigated. Multivariate experimental design was applied to study the growth and optical properties of obtained nanoparticles. Doehlert experimental design allowed determining the influence of three parameters (Synthesis temperature; synthesis period; and, initial concentration of precursors) on the different properties of the obtained nanoparticles; including: crystallite size obtained from Debby-Scherer calculation and bandgap energy obtained from optical absorption spectra of synthesized nanoparticles. Experimental data were fitted using artificial neural networks (ANNs). Also, the saliency of the input variables was measured using the connection weights of the neural networks in which the relative relevance of each variable with respect to the others was estimated. The ANN results indicated that the exciton band edge which was observed in UV-Vis spectra of the obtained nanoparticles due to confinement effects, by increasing the crystallite size the band gap shows shrinkage.

کلیدواژه ها:

Photonic Bandgap-Materials ، Nano Zinc Oxide ، Crystallite