Cookies ussage consent
Our site saves small pieces of text information (cookies) on your device in order to deliver better content and for statistical purposes. You can disable the usage of cookies by changing the settings of your browser. By browsing our site without changing the browser settings you grant us permission to store that information on your device.I agree, do not show this message again.
A. G. YUKSEK1, E. SENADIM TUZEMEN2,* , S. ELAGOZ3
- Department of Computer Engineering, Cumhuriyet University, 58140 Sivas, Turkey
- Nanophotonics Center, Department of Physics, Cumhuriyet University, 58140 Sivas, Turkey
- Nanophotonics Center, Department of Nanotechnology Engineering, Cumhuriyet University, 58140 Sivas, Turkey
A ZnO thin film was prepared on a p-Si (100) substrate by using a pulsed filtered cathodic vacuum arc deposition system (PFCVAD). Specular reflectance, a nondestructive technique, can be used to measure thickness, refractive index of thin films grown on reflecting substrate and their dependancy on reflecting angle. In this study, the effects of reflectance angle on specular reflectance measurements of ZnO thin film is modeled by Artificial Neural Networks (ANN) utilizing “ Multi-Layer Perceptron (MLP)”, Back propagation Algorithms Levenberg Marqued that is learning rule on incident angle range of 30-60 degrees. Also it is shown that reliable high precision measurements can be obtained without using expensive high precision hardware..
ZnO thin film, Artificial neural networks, Reflectance.
Submitted at: Jan. 20, 2015
Accepted at: Oct. 28, 2015
A. G. YUKSEK, E. SENADIM TUZEMEN, S. ELAGOZ, Modeling of reflectance properties of ZnO film using artificial neural networks, Journal of Optoelectronics and Advanced Materials Vol. 17, Iss. 11-12, pp. 1615-1628 (2015)
- Download Fulltext
- Downloads: 45 (from 29 distinct Internet Addresses ).