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Automated system for the detection of 2D materials using digital image processing and deep learning

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Articulo JCR (Open Access) (7.109Mb)
Date
2022-04-06
Author
Sanchez-Juarez, Jesús
Granados-Baez, Marissa
Aguilar Lasserre, Alberto Alfonso
Cárdenas, Jaime
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Abstract
The unique properties of two-dimensional materials for light emission, detection, and modulation make them ideal for integrated photonic devices. However, identifying if the films are indeed monolayers is a time-consuming process even for well-trained operators. We develop an intelligent algorithm to detect monolayers of WSe2, MoS2 and h-BN autonomously using Digital Image Processing and Deep Learning with high accuracy rate, avoiding human interaction and any additional characterization tests. We demonstrate an autonomous detection algorithm for TMDC’s and h-BN monolayers with high accuracy of 99.9% with a total processing time of 9 minutes per 1cm2. .
URI
http://repositorios.orizaba.tecnm.mx:8080/xmlui/handle/123456789/673
Temas
Automated system
Detection of 2D materials
Digital image processing
Deep learning
Tipo
Article
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  • Artículos (MII) [22]

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