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Vol. 32, No. 8(2), S&M2292

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Online: ISSN 2435-0869
Sensors and Materials
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Sensors and Materials, Volume 36, Number 1(1) (2024)
Copyright(C) MYU K.K.
pp. 17-23
S&M3494 Research Paper of Special Issue
https://doi.org/10.18494/SAM4506
Published: January 24, 2024

Machine Learning Techniques Applied to Development of Flexible Electronic Antireflective Film [PDF]

Shih-Hung Lin, Yuan-Ting Wang, and Yao-Chin Wang

(Received May 6, 2023; Accepted October 25, 2023)

Keywords: flexible substrates, antireflection, index matching, machine learning

In this study, we aim to optimize the process for developing antireflective and refractive-index-matching films on flexible substrates. The development of these films is crucial in light of the increasing demand in the market for flexible electronics, which are poised to be the next emerging technology and application after semiconductors and flat panel displays. Our research involves the production of these films by physical vapor deposition and sputtering techniques, which can also be applied to various optical thin films. The effectiveness of our coating process has been verified and refined on the basis of feedback. The results of this study are applicable to related industrial technologies and will contribute to improving industry competitiveness.

Corresponding author: Yao-Chin Wang


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Cite this article
Shih-Hung Lin, Yuan-Ting Wang, and Yao-Chin Wang, Machine Learning Techniques Applied to Development of Flexible Electronic Antireflective Film, Sens. Mater., Vol. 36, No. 1, 2024, p. 17-23.



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