Ultrasonic and artificial intelligence approach: Elastic behavior on the influences of ZnO in tellurite glass systems

Abstract Raise in the industrial development field required some simulation in order to predict the glass characterization before the pure materials of oxide are melted. This study uses artificial neural networks (ANN) model as a tool to simulate the elastic properties of the binary series ZnO-TeO2 glasses. This simulation would predict the density and elastic modulus variation include microhardness and Poisson’s ratio. The result from the ANN model was found to give an excellent good agreement with those experimental works of binary series xZnO-(100-x)TeO2 (x = 0, 5, 10, 15, 20, 25, 30 mol%) glass systems. From the ultrasonic wave measurement result, the substitution of ZnO which working as a network modifier towards TeO2 glass systems would break up the Te-O-Te bonds of TeO4 into the form TeO3 along with all the formation of NBO’s which give the impact in the elastic moduli analysis.