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http://dx.doi.org/10.4313/JKEM.2009.22.9.741

Modeling of Indium Tin Oxide(ITO) Film Deposition Process using Neural Network  

Min, Chul-Hong (가톨릭대학교 정보통신전자공학)
Park, Sung-Jin ((주)소로나)
Yoon, Neung-Goo ((주)소로나)
Kim, Tae-Seon (가톨릭대학교 정보통신전자공학)
Publication Information
Journal of the Korean Institute of Electrical and Electronic Material Engineers / v.22, no.9, 2009 , pp. 741-746 More about this Journal
Abstract
Compare to conventional Indium Tin Oxide (ITO) film deposition methods, cesium assisted sputtering method has been shown superior electrical, mechanical, and optical film properties. However, it is not easy to use cesium assisted sputtering method since ITO film properties are very sensitive to Cesium assisted equipment condition but their mechanism is not yet clearly defined physically or mathematically. Therefore, to optimize deposited ITO film characteristics, development of accurate and reliable process model is essential. For this, in this work, we developed ITO film deposition process model using neural networks and design of experiment (DOE). Developed model prediction results are compared with conventional statistical regression model and developed neural process model has been shown superior prediction results on modeling of ITO film thickness, sheet resistance, and transmittance characteristics.
Keywords
Indium tin oxide(lTO); Neural network; Process modeling; Statistical regression analysis; Cesium assisted sputtering;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
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