Oxygen Driven Defect Engineering of Monolayer MoS<sub>2</sub> for Tunable Electronic, Optoelectronic, and Electrochemical Devices
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Bibliographic record
Abstract
Abstract Molybdenum disulfide (MoS 2 ), a two‐dimensional (2D) semiconducting material harbors intrinsic defects that can be harnessed to achieve tuneable electronic, optoelectronic, and electrochemical devices. However, achieving precise control over defect formation within monolayer MoS 2 , remains a notable challenge. Here, an in‐situ defect engineering approach for monolayer MoS 2 using a pressure‐dependent chemical vapor deposition (CVD) process is presented. Monolayer MoS 2 grown in a low pressure CVD conditions (LP‐MoS 2 ) produces sulfur vacancy ( V s ) induced defect‐rich crystals primarily attributed to the oxygen‐deficient growth conditions. Conversely, atmospheric pressure CVD‐grown MoS 2 (AP‐MoS 2 ) passivates these defects with oxygen from ambient conditions. This disparity in defect profiles profoundly impacts crucial functional properties and device performance. AP‐MoS 2 shows a drastically enhanced photoluminescence, which is significantly quenched in LP‐MoS 2 attributed to in‐gap electron donor states induced by the V s defects. However, the n‐doping induced in LP‐MoS 2 generates enhanced photoresponsivity and detectivity in fabricated photodetectors compared to the AP‐MoS 2 ‐based devices. Defect‐rich LP‐MoS 2 outperforms AP‐MoS 2 as channel layers of field‐effect transistors (FETs), as well as electrocatalytic material for hydrogen evolution reaction (HER). This work presents a single‐step CVD approach for in situ defect engineering in monolayer MoS 2 and presents a pathway to control defects in other monolayer 2D materials.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it