Visualizing correlation between carrier mobility and defect density in MoS2 FET

Chen, Fu‐Xiang Rikudo; Kawakami, Nozomi; Lee, Chang‐Tsan; Shih, Pen-Yuan; Wu, Zi-Cheng; Yang, Yongcheng; Tu, Hao-Wei; Jian, Wen‐Bin; Hu, Chenming; Lin, Chun Liang

doi:10.1063/5.0107938

Cited by 11 publications

(11 citation statements)

References 45 publications

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“…It should be noted that no atomic defects are observed, which are expected to be easily accessible in STM images of MoS 2 layers. 52,54,55 Therefore, we conclude that the here deposited MoS 2 nanosheets are nearly defect free due to the chosen MOVPE deposition process.…”

Section: Resultsmentioning

confidence: 99%

The MoS₂-Graphene-Sapphire Heterostructure: Influence of Substrate Properties on the MoS₂ Band Structure

et al. 2023

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Van der Waals MoS2/graphene heterostructures are promising candidates for advanced electronics and optoelectronics beyond graphene. Herein, scanning probe methods and Raman spectroscopy were applied for analysis of the electronic and structural properties of monolayer (ML) and bilayer 2H-MoS2 deposited on single-layer graphene (SLG)-coated sapphire (S) substrates by means of an industrially scalable metal organic chemical vapor deposition process. The SLG/S substrate shows two regions with distinctly different morphology and varied interfacial coupling between SLG and S. ML MoS2 nanosheets grown on the almost free-standing graphene show no detectable interface coupling to the substrate, and a value of 2.23 eV for the MoS2 quasiparticle bandgap is determined. However, if the graphene is involved in hydrogen bonds to the hydroxylated sapphire surface, an increased MoS2/graphene interlayer coupling results, marked by a shift of the conduction band edge toward Fermi energy and a reduction of the ML MoS2 quasiparticle bandgap to 1.98 eV. The surface topography reveals a buckle structure of ML MoS2 in conformity with SLG that is used to determine the dependence of the ML MoS2 bandgap on the interfacial spacing of this heterostructure. In addition, an in-gap acceptor state about 0.9 eV above the valence band minimum of MoS2 has been observed on locally elevated positions on both SLG/S regions, which is attributed to local bending strain in the grown MoS2 nanosheets. These fundamental insights reveal the impact of the underlying substrate on the topography and the band alignment of the ML MoS2/SLG heterostructure and provide the possibility for engineering the quasiparticle bandgap of ML MoS2/SLG grown on controlled substrates that may impact the performance of electronic and optoelectronic devices therewith.

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Section: Resultsmentioning

confidence: 99%

The MoS₂-Graphene-Sapphire Heterostructure: Influence of Substrate Properties on the MoS₂ Band Structure

et al. 2023

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“…All images are scanned in constant current mode with −1 V sample bias and 1 nA tunneling current. By the help of this method, statistical property of defect density was researched 16 .…”

Section: Methodsmentioning

confidence: 99%

“…To prevent defects from affecting the performance of TMD devices, researchers usually use optical methods 11 , 12 , probing techniques 13 – 16 and transmission electron techniques 17 , 18 to measure the defect distribution on each TMD surface. Optical methods have advantages, such as large area and element detection, especially excellent in X-ray photoelectron spectroscopy measurement 19 .…”

Section: Background and Summarymentioning

confidence: 99%

Deep learning based atomic defect detection framework for two-dimensional materials

et al. 2023

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Defects to popular two-dimensional (2D) transition metal dichalcogenides (TMDs) seriously lower the efficiency of field-effect transistor (FET) and depress the development of 2D materials. These atomic defects are mainly identified and researched by scanning tunneling microscope (STM) because it can provide precise measurement without harming the samples. The long analysis time of STM for locating defects in images has been solved by combining feature detection with convolutional neural networks (CNN). However, the low signal-noise ratio, insufficient data, and a large amount of TMDs members make the automatic defect detection system hard to be applied. In this study, we propose a deep learning-based atomic defect detection framework (DL-ADD) to efficiently detect atomic defects in molybdenum disulfide (MoS2) and generalize the model for defect detection in other TMD materials. We design DL-ADD with data augmentation, color preprocessing, noise filtering, and a detection model to improve detection quality. The DL-ADD provides precise detection in MoS2 (F2-scores is 0.86 on average) and good generality to WS2 (F2-scores is 0.89 on average).

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“…The discrepancy could arise from intrinsic defects in TMD materials. Several studies have indicated that defects are largely responsible for the poor performance of TMD-derived devices. − For instance, a recent work has demonstrated the mobility of MoS 2 FET is correlated to the concentration of surface defects . Nevertheless, good control over the defects during sample preparation by either exfoliation or growth methods is nearly impossibleintrinsic defects are usually inevitable. − Many studies have attempted to control the numbers or types of defects after TMD samples are synthesized.…”

Section: Introductionmentioning

confidence: 99%

“…13−17 For instance, a recent work has demonstrated the mobility of MoS 2 FET is correlated to the concentration of surface defects. 17 Nevertheless, good control over the defects during sample preparation by either exfoliation or growth methods is nearly impossible� intrinsic defects are usually inevitable. 18−24 Many studies have attempted to control the numbers or types of defects after TMD samples are synthesized.…”

Section: Introductionmentioning

confidence: 99%

Toward Perfect Surfaces of Transition Metal Dichalcogenides with Ion Bombardment and Annealing Treatment

Chen

Kawakami

Hsueh

et al. 2023

ACS Appl. Mater. Interfaces

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Layered transition metal dichalcogenides (TMDs) are two-dimensional materials exhibiting a variety of unique features with great potential for electronic and optoelectronic applications. The performance of devices fabricated with mono or few-layer TMD materials, nevertheless, is significantly affected by surface defects in the TMD materials. Recent efforts have been focused on delicate control of growth conditions to reduce the defect density, whereas the preparation of a defect-free surface remains challenging. Here, we show a counterintuitive approach to decrease surface defects on layered TMDs: a two-step process including Ar ion bombardment and subsequent annealing. With this approach, the defects, mainly Te vacancies, on the as-cleaved PtTe 2 and PdTe 2 surfaces were decreased by more than 99%, giving a defect density <1.0 × 10 10 cm −2 , which cannot be achieved solely with annealing. We also attempt to propose a mechanism behind the processes.

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Visualizing correlation between carrier mobility and defect density in MoS2 FET

Cited by 11 publications

References 45 publications

The MoS₂-Graphene-Sapphire Heterostructure: Influence of Substrate Properties on the MoS₂ Band Structure

The MoS₂-Graphene-Sapphire Heterostructure: Influence of Substrate Properties on the MoS₂ Band Structure

Deep learning based atomic defect detection framework for two-dimensional materials

Toward Perfect Surfaces of Transition Metal Dichalcogenides with Ion Bombardment and Annealing Treatment

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Visualizing correlation between carrier mobility and defect density in MoS2 FET

Cited by 11 publications

References 45 publications

The MoS2-Graphene-Sapphire Heterostructure: Influence of Substrate Properties on the MoS2 Band Structure

The MoS2-Graphene-Sapphire Heterostructure: Influence of Substrate Properties on the MoS2 Band Structure

Deep learning based atomic defect detection framework for two-dimensional materials

Toward Perfect Surfaces of Transition Metal Dichalcogenides with Ion Bombardment and Annealing Treatment

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Product

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The MoS₂-Graphene-Sapphire Heterostructure: Influence of Substrate Properties on the MoS₂ Band Structure

The MoS₂-Graphene-Sapphire Heterostructure: Influence of Substrate Properties on the MoS₂ Band Structure