Real-Time Observation of Photo-oxidation of Single MoS<sub>2</sub> Flakes Using Stochastic Optical Reconstruction Microscopy
Bibliographic record
Abstract
We report on molybdenum disulfide (MoS 2 ) flakes grown by chemical vapor deposition (CVD), which exhibit an increased photoluminescence (PL) intensity at the edge of the flake under moderate irradiation. The photo-induced chemisorption of O 2 and H 2 O to sulfur vacancies in the edge regions is the origin of the modulated PL intensity. The MoS 2 flakes were analyzed utilizing correlated multispectral wide-field microscopy with stochastic optical reconstruction microscopy (STORM). The advantage of the wide-field approach compared to conventional point scanning microscopy is a faster acquisition over a larger field of view without exposing the sample to high irradiance conditions. This enables in situ and real-time measurements of the PL intensity fluctuations and the identification of defects within the flake. The STORM postprocessing reveals fine structures within the flake and enhances the contrast, which cannot be revealed by point scanning microscopy. In particular, by increasing the intensity over the nondestructive threshold, the stochastic optical reconstruction enables the study of the kinetics of defect domain generation with reduced PL and Raman intensity caused by lattice defects or photo-oxidation of MoS 2 to MoO 3 . Additional measurements of the work function by Kelvin force microscopy, the topography, and the friction force by AFM reveal that the defect domains start to form at the edge of the flake, with a larger interlayer height and work function but reduced friction force compared to MoS 2 . The stochastic optical reconstruction microscopy postprocessing is a powerful technique to understand the layer-by-layer photo-oxidation of MoS 2 flakes and gives new insights in the design of, for example, MoS 2 /MoO 3 heterostructures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".