Modeling and optimization of ITO/Al/ITO multilayer films characteristics using neural network and genetic algorithm

Authors:
Edward Namkyu Cho;Pyung Moon;Chang Eun Kim;Ilgu Yun
Affiliations:
Department of Electrical and Electronic Engineering, 50 Yonsei-ro, Seodaemun-gu, Yonsei University, Seoul 120-749, Republic of Korea;Department of Electrical and Electronic Engineering, 50 Yonsei-ro, Seodaemun-gu, Yonsei University, Seoul 120-749, Republic of Korea;Department of Electrical and Electronic Engineering, 50 Yonsei-ro, Seodaemun-gu, Yonsei University, Seoul 120-749, Republic of Korea;Department of Electrical and Electronic Engineering, 50 Yonsei-ro, Seodaemun-gu, Yonsei University, Seoul 120-749, Republic of Korea
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Expert Systems with Applications: An International Journal

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Abstract

In this paper, ITO/Al/ITO multilayer films are fabricated with the variations of Al film thickness and annealing temperature. The effects of Al film thickness and annealing temperature on sheet resistance, optical transmittance, and the figure of merit are analyzed in the aid of the artificial neural network (NNet) models. In order to verify the fitness of NNet model, the root mean square error (RMSE) of training and testing data are calculated. The NNet models well represent the measured sheet resistance, optical transmittance, and the figure of merit. After NNet model is established, genetic algorithm (GA) is used to find the optimum process condition for the ITO/Al/ITO multilayer films to obtain maximum figure of merit in the design space.