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 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 | 0.001 | 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 teacher head, 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".