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Direct observation of the CVD growth of monolayer MoS₂ using in situ optical spectroscopy.

ABSTRACT: Real-time monitoring is essential for understanding and precisely controlling of growth of two-dimensional transition metal dichalcogenide (2D TMDC) materials. However, it is very challenging to carry out such studies during chemical vapor deposition (CVD). Here, we report the first, real time, in situ study of the CVD growth of 2D TMDCs. More specifically, the CVD growth of a molybdenum disulfide (MoS₂) monolayer on sapphire substrates has been monitored in situ using differential transmittance spectroscopy (DTS). The growth of the MoS₂ monolayer can be precisely followed by observation of the evolution of the characteristic optical features. Consequently, a strong correlation between the growth rate of the MoS₂ monolayer and the temperature distribution in the CVD reactor has been revealed. Our results demonstrate the great potential of real time, in situ optical spectroscopy to assist the precisely controlled growth of 2D semiconductor materials.

SUBMITTER: Lopez-Posadas CB

PROVIDER: S-EPMC6404415 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Direct observation of the CVD growth of monolayer MoS<sub>2</sub> using in situ optical spectroscopy.

López-Posadas Claudia Beatriz CB Wei Yaxu Y Shen Wanfu W Kahr Daniel D Hohage Michael M Sun Lidong L

Beilstein journal of nanotechnology 20190226

Real-time monitoring is essential for understanding and precisely controlling of growth of two-dimensional transition metal dichalcogenide (2D TMDC) materials. However, it is very challenging to carry out such studies during chemical vapor deposition (CVD). Here, we report the first, real time, in situ study of the CVD growth of 2D TMDCs. More specifically, the CVD growth of a molybdenum disulfide (MoS<sub>2</sub>) monolayer on sapphire substrates has been monitored in situ using differential tr ...[more]

PMID: 30873328

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Project description:BackgroundIn Complementary Metal-Oxide Semiconductor (CMOS) technology, scaling down has been a key strategy to improve chip performance and reduce power losses. However, challenges such as sub-threshold leakage and gate leakage, resulting from short-channel effects, contribute to an increase in distributed static power. Two-dimensional transition metal dichalcogenides (2D TMDs) emerge as potential solutions, serving as channel materials with steep sub-threshold swings and lower power consumption. However, the production and development of these 2-dimensional materials require some time-consuming tasks. In order to employ them in different fields, including chip technology, it is crucial to ensure that their production meets the required standards of quality and uniformity; in this context, deep learning techniques show significant potential.MethodsThis research introduces a transfer learning-based deep convolutional neural network (CNN) to classify chemical vapor deposition (CVD) grown molybdenum disulfide (MoS2) flakes based on their uniformity or the occurrence of defects affecting electronic properties. Acquiring and labeling a sufficient number of microscope images for CNN training may not be realistic. To address this challenge, artificial images were generated using Fresnel equations to pre-train the CNN. Subsequently, accuracy was improved through fine-tuning with a limited set of real images.ResultsThe proposed transfer learning-based CNN method significantly improved all measurement metrics with respect to the ordinary CNNs. The initial CNN, trained with limited data and without transfer learning, achieved 68% average accuracy for binary classification. Through transfer learning and artificial images, the same CNN achieved 85% average accuracy, demonstrating an average increase of approximately 17%. While this study specifically focuses on MoS2 structures, the same methodology can be extended to other 2-dimensional materials by simply incorporating their specific parameters when generating artificial images.

Dataset Information

Direct observation of the CVD growth of monolayer MoS₂ using in situ optical spectroscopy.

Publications

Direct observation of the CVD growth of monolayer MoS<sub>2</sub> using in situ optical spectroscopy.

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Dataset Information

Direct observation of the CVD growth of monolayer MoS2 using in situ optical spectroscopy.

Publications

Direct observation of the CVD growth of monolayer MoS<sub>2</sub> using in situ optical spectroscopy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Direct observation of the CVD growth of monolayer MoS₂ using in situ optical spectroscopy.