Metallic thin films are essential for various device applications. Given that sensor performance highly depends on thin film thickness and optical constants, ellipsometry is an indispensable measurement technique. While a cost-effective alternative using a spectrometer exists, it is cannot simultaneously determine both thickness and optical constants. In this study, we develop and validate a machine learning model capable of simultaneously estimating film thickness and optical constants from a single reflectance spectrum, thereby extending its applicability to opaque substrates and materials for which conventional models are inadequate.
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