Quantitative Defect Analysis in CVD‐Grown Monolayer MoS2 via In‐Plane Raman Vibration

ABSTRACT The synthesis of two‐dimensional transition metal dichalcogenide (2D‐TMD) materials gives rise to inherent defects, specifically chalcogen vacancies, due to thermodynamic equilibrium. Techniques such as chemical vapor deposition (CVD), metal‐organic chemical vapor deposition (MOCVD), atomic...

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Bibliographic Details
Main Authors: Moha Feroz Hossen, Sachin Shendokar, Md. Arifur Rahman Khan, Shyam Aravamudhan
Format: Article
Language:English
Published: Wiley-VCH 2025-04-01
Series:Nano Select
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Online Access:https://doi.org/10.1002/nano.202400103
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Summary:ABSTRACT The synthesis of two‐dimensional transition metal dichalcogenide (2D‐TMD) materials gives rise to inherent defects, specifically chalcogen vacancies, due to thermodynamic equilibrium. Techniques such as chemical vapor deposition (CVD), metal‐organic chemical vapor deposition (MOCVD), atomic layer deposition (ALD), flux growth method, and mechanical exfoliation produce large‐scale, uniform 2D TMD films, either in bulk or monolayers. However, defects on the film surface impact its quality, and it is necessary to measure defect density. The phonon confinement model indicates that the first‐order Raman band frequency shift depends on defect density. Monolayer Molybdenum disulfide (MoS2) exhibits three phonon dispersions at the Brillouin zone edge (M point): out‐of‐plane optical phonon vibration (ZO), in‐plane longitudinal optical phonon vibration (LO), and in‐plane transverse optical phonon vibration (TO). The LO and ZO modes overlap with Raman in‐plane vibration (𝐸12g) and Raman out‐of‐plane vibration (𝐴1g), respectively, causing peak broadening. In the presence of defects, the Raman 𝐸12g vibration energy decreases due to a reduced restoring force constant. The Raman 𝐴1g vibration trend is random, influenced by both restoring force constant and mass. The study introduces a quantitative defect measurement technique for CVD‐grown monolayer MoS2 using Raman 𝐸12g mode, employing sequential data processing algorithms to reveal defect density on the film surface.
ISSN:2688-4011