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

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 t...

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Bibliographic Details
Published inOptical materials express Vol. 12; no. 5; p. 1856
Main Authors Sanchez-Juarez, Jesus, Granados-Baez, Marissa, Aguilar-Lasserre, Alberto A., Cardenas, Jaime
Format Journal Article
LanguageEnglish
Published Washington Optical Society of America 01.05.2022
Subjects
Algorithms
Deep learning
Digital imaging
Image processing
Light emission
Machine learning
Monolayers
Two dimensional materials
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Summary: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 WSe 2 , MoS 2 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 1 cm 2 .
ISSN:2159-3930
2159-3930
DOI:10.1364/OME.454314