In-Situ Generation of Nitrogen-Doped MoS2 Quantum Dots Using Laser Ablation in Cryogenic Medium for Hydrogen Evolution Reaction
Bibliographic record
Abstract
Here, nitrogen doped molybdenum disulfide quantum dots (N-MoS2 QDs) are fabricated by making use of the pulsed laser ablation (PLA) process in liquid nitrogen (LN2) as a dopant agent. In fact, LN2 contributes the rapid condensation of the plasma plume to form MoS2 QDs, optimizing the conditions for the synthesis of N-doped MoS2 with p-type property. The structural/optical features of the synthesized products are studied using transmission electron microscopy (TEM), absorption spectroscopy, photoluminescence (PL) spectroscopy techniques, and X-ray photoelectron spectroscopy (XPS). The TEM image shows the creation of MoS2 QDs with 5.5 nm average size. UV-vis and PL spectroscopy confirm the formation of N-MoS2 QDs according to the dominant peaks. The Tuck plot gives a direct band-gap of 4.34 eV for MoS2 QDs. Furthermore, XPS spectroscopy reveals Mo-N bonding, indicating nitrogen doping as evidence of p-type MoS2 QDs. Thus, PLA provides a single-stage way to the clean and green synthesis of the MoS2 QDs suspension without a need for high vacuum devices and additional chemical components. Regarding the pristine MoS2, the N-MoS2 QDs benefit from a low overpotential of −0.35 V at −10 mA/cm2 per µg alongside a low Tafel slope of 300 mV/dec. Subsequently, the lower Rct value of N-MoS2 QDs verifies the enhancement of the charge transfer kinetics mainly due to the elevated electronic conductivity. Furthermore, the quasi-rectangular cyclic voltammetry (CV) as well as the larger current window demonstrate a notable electrocatalytic activity. The former is based on the enhanced active sites in favor of N-MoS2 QDs against other samples of interest. Thereby, it is discovered that the N-doped MoS2 QD acts as an effective catalyst to notably improve the performance of the hydrogen evolution reaction (HER).
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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".