Process estimation and optimized recipes of ZnO: Ga thin film characteristics for transparent electrode applications

Authors:
Chang Eun Kim;Pyung Moon;Ilgu Yun;Sungyeon Kim;Jae-Min Myoung;Hyeon Woo Jang;Jungsik Bang
Affiliations:
School of Electrical and Electronic Engineering, Yonsei University, 262, Seongsanno, Seodaemoon-gu, Seoul 120-749, Republic of Korea;School of Electrical and Electronic Engineering, Yonsei University, 262, Seongsanno, Seodaemoon-gu, Seoul 120-749, Republic of Korea;School of Electrical and Electronic Engineering, Yonsei University, 262, Seongsanno, Seodaemoon-gu, Seoul 120-749, Republic of Korea;Department of Materials Science and Engineering, Yonsei University, 262, Seongsanno, Seodaemoon-gu, Seoul 120-749, Republic of Korea;Department of Materials Science and Engineering, Yonsei University, 262, Seongsanno, Seodaemoon-gu, Seoul 120-749, Republic of Korea;LG Chem, Ltd./Research Park, 104-1 Moonji-Dong, Yuseng-Gu, Daejeon 305-380, Republic of Korea;LG Chem, Ltd./Research Park, 104-1 Moonji-Dong, Yuseng-Gu, Daejeon 305-380, Republic of Korea
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Modeling and optimization of the growth rate for ZnO thin films using neural networks and genetic algorithms

Expert Systems with Applications: An International Journal

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Abstract

Ga-doped zinc oxide (ZnO:Ga) thin films were prepared on glass substrate by magnetron sputtering at room temperature (RT) and thermally annealed in hydrogen atmosphere for 1h. The effects of film thickness and annealing temperature on sheet resistance, transmittance and figure of merit of ZnO:Ga thin films were analyzed and modeled using the artificial neural networks (NNets). The NNet models presented the good prediction on sheet resistance, transmittance and figure of merit of ZnO:Ga thin films and it was found that the electrical and optical properties of ZnO:Ga thin films were enhanced by thermal annealing. After NNet models were verified, genetic algorithm (GA) was used to search the optimized recipe for the desired figure of merit of ZnO:Ga thin films. The methodology allows us to estimate the optimal process condition with a small number of experiments.