期刊
OPTICAL MATERIALS EXPRESS
卷 12, 期 5, 页码 1856-1868出版社
Optica Publishing Group
DOI: 10.1364/OME.454314
关键词
-
资金
- Institute of Optics of the University of Rochester
Researchers have developed an intelligent algorithm that can autonomously detect monolayers of two-dimensional materials with high accuracy using digital image processing and deep learning, avoiding human intervention and additional tests.
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 1cm(2). (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
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