Optical constants characterization of As30Se70−xSnx thin films using neural networks

This paper uses an artificial neural network (ANN) and resilient back-propagation (Rprop) training algorithm to determine the optical constants of As30Se70−xSnx (0 ≤ x ≤ 3) thin films. The simulated values of the ANN are in good agreement with the experimental data. The ANN models performance was also examined to predict the simulated values for As30Se67Sn3 which was not included in the training and was found to be in accordance with the experimental data. The high precision of the ANN models as well as a great guessing performance have been exhibited. Moreover, the energy gap Eg of As30Se70−xSnx (0 ≤ x ≤ 9) thin films were calculated theoretically.