DocumentCode :
3694456
Title :
Computational intelligence technique in optimization of nano-process deposition parameters
Author :
M. S. Norlina;P. Mazidah;N. D. Md Sin;M. Rusop
Author_Institution :
Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA (Terengganu), Dungun, Terengganu, Malaysia
fYear :
2015
Firstpage :
184
Lastpage :
188
Abstract :
This paper is focusing on the RF magnetron sputtering process; a physical vapor deposition technique which is widely used in the thin film production. This process requires the optimized combination of deposition parameters in order to obtain the desirable thin film. This research is proposing gravitational search algorithm (GSA) technique in solving the RF magnetron sputtering deposition parameters optimization problem. In this research, the optimized parameter combination is expected to produce the desirable electrical and optical properties of the thin film. The performance of GSA in this research was compared with that of PSO and GA. Based on the overall result, the thin film that has been deposited based on GSA optimized parameter combination has generated the best electrical and optical properties results among others. This computational experiment is expected to overcome the problem of having to conduct repetitive laboratory experiments in order to obtain the most optimized parameter combination. Thus, the adaptation of computational intelligence into this problem could offer a more efficient and productive way of depositing quality thin film.
Keywords :
"Optimization","Sputtering","Optical films","Radio frequency","Adaptive optics","Conductivity","Computational intelligence"
Publisher :
ieee
Conference_Titel :
Computer Science and Electronic Engineering Conference (CEEC), 2015 7th
Type :
conf
DOI :
10.1109/CEEC.2015.7332722
Filename :
7332722
Link To Document :
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