Evaluation of optical constants in oxide thin films using machine learning
Kyosuke Saeki,
Takayuki Makino
Abstract:This paper describes an inverse analysis method using neural networks on optical spectroscopy, and its application to the quantitative optical constant evaluation. The present method consists of three subprocesses. First, measurable UV–visible spectroscopic quantities were calculated as functions of the optical constants of the solid based on the Tomlin equations [J. Phys. D 1 1667 (1968)] by carefully eliminating the unpractical combinations of optical constants. Second, the backpropagation neural network is … Show more
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