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Conferences > CLEO_SI > 2021 > JTh3A > JTh3A.8

Thickness identification of 2D materials by machine learning assisted optical microscopy

Daniele Gaetano Sirico, Giovanni Acampora, Pasqualino Maddalena, and Felice Gesuele

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Abstract

We report a rapid and cost-effective method for the identification of the thickness of two-dimensional materials such as transition metal dichalcogenides. Our technique is based on the analysis of the optical contrast by means of machine learning algorithms and it is well suited for accurate characterization of 2D materials over large areas.

© 2021 The Author(s)

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