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Nano Research 2021, 14(3): 840-845 https://doi.org/10.1007/s12274-020-3122-0
Research Article | Issue | Published: 01 March 2021

Rapid thin-layer WS2 detection based on monochromatic illumination photographs

Show Author's Information Xiangmin Hu,  Cuicui Qiu,  Dameng Liu( )
State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China
Keywords:
image recognition, WS2, thickness identification, sample detection
Topics:
Nanostructured materialsOptoelectronic devicesTungsten compounds
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Hu X, Qiu C, Liu D. Rapid thin-layer WS2 detection based on monochromatic illumination photographs. Nano Research, 2021, 14(3): 840-845. https://doi.org/10.1007/s12274-020-3122-0
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Abstract Full text Electronic supplementary material About this article

The thickness of two-dimensional (2D) nanomaterials shows a significant effect on their optical and electrical properties. Therefore, a rapid and automatic detection technology of 2D nanomaterials with desired layer-number is required to extend their practical application in optoelectronic devices. In this paper, an image recognition technology was proposed for rapid and reliable identification of thin-layer WS2 samples, which combining a layer-thickness identification criterion and a novel image segmentation algorithm. The criterion stemmed from optical contrast study of monochromatic illumination photographs, and the algorithm was based on Canny operator and edge connection iteration. This optical identification method can seek out thin-layer WS2 samples on complex surfaces, which provides a promising approach for automatic search of thin-layer nanomaterials.


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About this article

Rapid thin-layer WS2 detection based on monochromatic illumination photographs

Show Author's information Xiangmin Hu, Cuicui Qiu, Dameng Liu( )
State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China

Abstract

The thickness of two-dimensional (2D) nanomaterials shows a significant effect on their optical and electrical properties. Therefore, a rapid and automatic detection technology of 2D nanomaterials with desired layer-number is required to extend their practical application in optoelectronic devices. In this paper, an image recognition technology was proposed for rapid and reliable identification of thin-layer WS2 samples, which combining a layer-thickness identification criterion and a novel image segmentation algorithm. The criterion stemmed from optical contrast study of monochromatic illumination photographs, and the algorithm was based on Canny operator and edge connection iteration. This optical identification method can seek out thin-layer WS2 samples on complex surfaces, which provides a promising approach for automatic search of thin-layer nanomaterials.

Keywords: image recognition, WS2, thickness identification, sample detection

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Publication history
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Acknowledgements

Publication history

Received: 04 August 2020
Revised: 09 September 2020
Accepted: 15 September 2020
Published: 01 March 2021
Issue date: March 2021

Copyright

© Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature

Acknowledgements

We acknowledge support from the National Natural Science Foundation of China (nos. 51527901, 11890672, and 51705285).

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