Spatially Selective Enhancement of Photoluminescence in MoS<sub>2</sub> by Exciton-Mediated Adsorption and Defect Passivation
Bibliographic record
Abstract
Monolayers of transition-metal dichalcogenides (TMDs) are promising components for flexible optoelectronic devices because of their direct band gap and atomically thin nature. The photoluminescence (PL) from these materials is often strongly suppressed by nonradiative recombination mediated by midgap defect states. Here, we demonstrate up to a 200-fold increase in PL intensity from monolayer MoS 2 synthesized by chemical vapor deposition (CVD) by controlled exposure to laser light in the ambient. This spatially resolved passivation treatment is stable in air and vacuum. Regions unexposed to laser light remain dark in fluorescence despite continuous impingement of ambient gas molecules. A wavelength-dependent study confirms that PL brightening is concomitant with exciton generation in the MoS 2; laser light below the optical band gap fails to produce any enhancement in the PL. We highlight the photosensitive nature of the process by successfully brightening with a low-power broadband white light source. We decouple changes in absorption from defect passivation by examining the degree of circularly polarized PL. This measurement, which is independent of exciton generation, confirms that laser brightening reduces the rate of nonradiative recombination in the MoS 2 . A series of gas exposure studies demonstrate a clear correlation between PL brightening and the presence of water. We propose that H 2 O molecules passivate sulfur vacancies in the CVD-grown MoS 2 but require photogenerated excitons to overcome a large adsorption barrier. This work represents an important step in understanding the passivation of CVD-synthesized TMDs and demonstrates the interplay between adsorption and exciton generation.
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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) | 0.001 | 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".