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Barrier-assisted vapor phase CVD of large-area MoS₂ monolayers with high spatial homogeneity.

ABSTRACT: Atomically thin molybdenum disulphide (MoS₂) is a direct band gap semiconductor with negatively charged trions and stable excitons in striking contrast to the wonder material graphene. While large-area growth of MoS₂ can be readily achieved by gas-phase chemical vapor deposition (CVD), growth of continuous MoS₂ atomic layers with good homogeneity is indeed one of the major challenges in vapor-phase CVD involving all-solid precursors. In this study, we demonstrate the growth of large-area continuous single crystal MoS₂ monolayers on c-plane sapphire by carefully positioning the substrate using a facile staircase-like barrier. The barrier offered great control in mitigating the secondary and intermediate phases as well as second layer nucleation, and eventually a continuous monolayer with high surface homogeneity is realized. Both micro-Raman and high-resolution transmission electron microscopy (HRTEM) results confirmed the high structural quality of the grown MoS₂ layers. Using low temperature photoluminescence spectroscopy, additional pieces of information are provided for the strong band-edge emission in the light of vacancy compensation and formation of Mo-O bonding. The monolayer MoS₂ transferred to SiO₂/Si exhibited a room temperature field-effect mobility of ∼1.2 cm² V^-1 s^-1 in a back-gated two-terminal configuration.

SUBMITTER: Durairaj S

PROVIDER: S-EPMC9418203 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Barrier-assisted vapor phase CVD of large-area MoS2 monolayers with high spatial homogeneity.

Durairaj Santhosh S Krishnamoorthy P P Raveendran Navanya N Ryu Beo Deul BD Hong Chang-Hee CH Seo Tae Hoon TH Chandramohan S S

Nanoscale advances 20200709 9

Atomically thin molybdenum disulphide (MoS2) is a direct band gap semiconductor with negatively charged trions and stable excitons in striking contrast to the wonder material graphene. While large-area growth of MoS2 can be readily achieved by gas-phase chemical vapor deposition (CVD), growth of continuous MoS2 atomic layers with good homogeneity is indeed one of the major challenges in vapor-phase CVD involving all-solid precursors. In this study, we demonstrate ...[more]

PMID: 36132761

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Project description:Molybdenum disulfide (MoS2) is a layered transition metal-sulfur compound semiconductor that shows promising prospects for applications in optoelectronics and integrated circuits because of its low preparation cost, good stability and excellent physicochemical, biological and mechanical properties. MoS2 with high quality, large size and outstanding performance can be prepared via chemical vapor deposition (CVD). However, its preparation process is complex, and the area of MoS2 obtained is difficult to control. Machine learning (ML), as a powerful tool, has been widely applied in materials science. Based on this, in this paper, a ML Gaussian regression model was constructed to explore the growth mechanism of MoS2 material prepared with the CVD method. The parameters of the regression model were evaluated by combining the four indicators of goodness of fit (r2), mean squared error (MSE), Pearson correlation coefficient (p) and p-value (p_val) of Pearson's correlation coefficient. After comprehensive comparison, it was found that the performance of the model was optimal when the number of iterations was 15. Additionally, feature importance analysis was conducted on the growth parameters using the established model. The results showed that the carrier gas flow rate (Fr), molybdenum sulfur ratio (R) and reaction temperature (T) had a crucial impact on the CVD growth of MoS2 materials. The optimal model was used to predict the size of molybdenum disulfide synthesis under 185,900 experimental conditions in the simulation dataset so as to select the optimal range for the synthesis of large-size molybdenum disulfide. Furthermore, the model prediction results were verified through literature and experimental results. It was found that the relative error between the prediction results and the literature and experimental results was small. These findings provide an effective solution to the preparation of MoS2 materials with a reduction in the time and cost of trial and error.

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Barrier-assisted vapor phase CVD of large-area MoS₂ monolayers with high spatial homogeneity.

Publications

Barrier-assisted vapor phase CVD of large-area MoS<sub>2</sub> monolayers with high spatial homogeneity.

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