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

Edward Namkyu Cho, Pyung Moon, Chang Eun Kim, Ilgu Yun

Research output: Contribution to journalArticle

17 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)8885-8889
Number of pages5
JournalExpert Systems with Applications
Volume39
Issue number10
DOIs
Publication statusPublished - 2012 Aug 1

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Modeling and optimization of ITO/Al/ITO multilayer films characteristics using neural network and genetic algorithm'. Together they form a unique fingerprint.

  • Cite this