Optimization of Nano-Process Deposition Parameters Based on Gravitational Search Algorithm

This research is focusing on the radio frequency (RF) magnetron sputtering process, a physical vapor deposition technique which is widely used in thin film production. This process requires the optimized combination of deposition parameters in order to obtain the desirable thin film. The conventiona...

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Main Authors: Norlina Mohd Sabri, Nor Diyana Md Sin, Mazidah Puteh, Mohamad Rusop Mahmood
Format: Article
Language:English
Published: MDPI AG 2016-06-01
Series:Computers
Subjects:
Online Access:http://www.mdpi.com/2073-431X/5/2/12
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spelling doaj-0249331078b645d4b441d3b6cc4c45492020-11-25T00:03:02ZengMDPI AGComputers2073-431X2016-06-01521210.3390/computers5020012computers5020012Optimization of Nano-Process Deposition Parameters Based on Gravitational Search AlgorithmNorlina Mohd Sabri0Nor Diyana Md Sin1Mazidah Puteh2Mohamad Rusop Mahmood3Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA (Terengganu), 23000 Dungun, MalaysiaNANO-ElecTronic Centre, Faculty of Electrical Engineering, Universiti Teknologi MARA, 40450 Shah Alam, MalaysiaFaculty of Computer and Mathematical Sciences, Universiti Teknologi MARA (Terengganu), 23000 Dungun, MalaysiaNANO-ElecTronic Centre, Faculty of Electrical Engineering, Universiti Teknologi MARA, 40450 Shah Alam, MalaysiaThis research is focusing on the radio frequency (RF) magnetron sputtering process, a physical vapor deposition technique which is widely used in thin film production. This process requires the optimized combination of deposition parameters in order to obtain the desirable thin film. The conventional method in the optimization of the deposition parameters had been reported to be costly and time consuming due to its trial and error nature. Thus, gravitational search algorithm (GSA) technique had been proposed to solve this nano-process parameters optimization problem. In this research, the optimized parameter combination was 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 Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Artificial Immune System (AIS) and Ant Colony Optimization (ACO). Based on the overall results, the GSA optimized parameter combination had generated the best electrical and an acceptable optical properties of thin film compared to the others. This computational experiment is expected to overcome the problem of having to conduct repetitive laboratory experiments in obtaining the most optimized parameter combination. Based on this initial experiment, the adaptation of GSA into this problem could offer a more efficient and productive way of depositing quality thin film in the fabrication process.http://www.mdpi.com/2073-431X/5/2/12gravitational search algorithmoptimizationmagnetron sputtering processdeposition parameters
collection DOAJ
language English
format Article
sources DOAJ
author Norlina Mohd Sabri
Nor Diyana Md Sin
Mazidah Puteh
Mohamad Rusop Mahmood
spellingShingle Norlina Mohd Sabri
Nor Diyana Md Sin
Mazidah Puteh
Mohamad Rusop Mahmood
Optimization of Nano-Process Deposition Parameters Based on Gravitational Search Algorithm
Computers
gravitational search algorithm
optimization
magnetron sputtering process
deposition parameters
author_facet Norlina Mohd Sabri
Nor Diyana Md Sin
Mazidah Puteh
Mohamad Rusop Mahmood
author_sort Norlina Mohd Sabri
title Optimization of Nano-Process Deposition Parameters Based on Gravitational Search Algorithm
title_short Optimization of Nano-Process Deposition Parameters Based on Gravitational Search Algorithm
title_full Optimization of Nano-Process Deposition Parameters Based on Gravitational Search Algorithm
title_fullStr Optimization of Nano-Process Deposition Parameters Based on Gravitational Search Algorithm
title_full_unstemmed Optimization of Nano-Process Deposition Parameters Based on Gravitational Search Algorithm
title_sort optimization of nano-process deposition parameters based on gravitational search algorithm
publisher MDPI AG
series Computers
issn 2073-431X
publishDate 2016-06-01
description This research is focusing on the radio frequency (RF) magnetron sputtering process, a physical vapor deposition technique which is widely used in thin film production. This process requires the optimized combination of deposition parameters in order to obtain the desirable thin film. The conventional method in the optimization of the deposition parameters had been reported to be costly and time consuming due to its trial and error nature. Thus, gravitational search algorithm (GSA) technique had been proposed to solve this nano-process parameters optimization problem. In this research, the optimized parameter combination was 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 Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Artificial Immune System (AIS) and Ant Colony Optimization (ACO). Based on the overall results, the GSA optimized parameter combination had generated the best electrical and an acceptable optical properties of thin film compared to the others. This computational experiment is expected to overcome the problem of having to conduct repetitive laboratory experiments in obtaining the most optimized parameter combination. Based on this initial experiment, the adaptation of GSA into this problem could offer a more efficient and productive way of depositing quality thin film in the fabrication process.
topic gravitational search algorithm
optimization
magnetron sputtering process
deposition parameters
url http://www.mdpi.com/2073-431X/5/2/12
work_keys_str_mv AT norlinamohdsabri optimizationofnanoprocessdepositionparametersbasedongravitationalsearchalgorithm
AT nordiyanamdsin optimizationofnanoprocessdepositionparametersbasedongravitationalsearchalgorithm
AT mazidahputeh optimizationofnanoprocessdepositionparametersbasedongravitationalsearchalgorithm
AT mohamadrusopmahmood optimizationofnanoprocessdepositionparametersbasedongravitationalsearchalgorithm
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