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.
Thickness identification of 2D materials by machine learning assisted optical microscopy / Sirico, D. G.; Acampora, G.; Maddalena, P.; Gesuele, F.. - (2021). (Intervento presentato al convegno 2021 Conference on Lasers and Electro-Optics, CLEO 2021 tenutosi a usa nel 2021).
Thickness identification of 2D materials by machine learning assisted optical microscopy
Acampora G.;Maddalena P.;Gesuele F.
2021
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.File in questo prodotto:
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