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Journal of applied research and technology
On-line version ISSN 2448-6736Print version ISSN 1665-6423
Abstract
ATTIA, Attia A. et al. Optical constants characterization of As30Se 70−x Sn x thin films using neural networks. J. appl. res. technol [online]. 2017, vol.15, n.5, pp.423-429. ISSN 2448-6736. https://doi.org/10.1016/j.jart.2017.03.009.
This paper uses an artificial neural network (ANN) and resilient back-propagation (Rprop) training algorithm to determine the optical constants of As30Se 70−x Sn x (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 E g of As30Se 70−x Sn x (0 ≤ x ≤ 9) thin films were calculated theoretically.
Keywords : ANN model; Optical constants; Energy gap.