Vacuum and Surface Science
Online ISSN : 2433-5843
Print ISSN : 2433-5835
Special Feature : Transactions of the Annual Meeting on the Japan Society of Vacuum and Surface Science 2018 [III]
Validation with Measured Data of Photoelectron Yield Spectroscopy (PYS) Threshold Using Machine Learning
Shinjiro YAGYU Michiko YOSHITAKEToyohiro CHIKYOWTakahiro NAGATA
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2019 Volume 62 Issue 8 Pages 504-510

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Abstract

In order to estimate the threshold of photoelectron yield spectroscopy (PYS), regression estimator was created by machine learning using calculation data based on Fowler's theory. We compared verification data with the prediction by regression estimators. The verification data measured by AC-3 instrument manufactured by Riken Keiki Co. are the number of 87 (Au : 31, Metals except for Au : 16, oxide · semiconductor : 15, organic : 25) with estimate value by analyst (label data). As a result, the prediction performance was 70% over in the range of difference between label data and estimation from ±0.2 eV. On the other hand, spectra in the difference of 0.3 eV were included in difficult labeling by analysts. The prediction by machine learning gives the guide to analysis.

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この記事はクリエイティブ・コモンズ [表示 - 非営利 4.0 国際]ライセンスの下に提供されています。
https://creativecommons.org/licenses/by-nc/4.0/deed.ja
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