Synthesis, Characterization, and Typical Application of Nitrogen‐Doped MoS<sub>2</sub> Nanosheets Based on Pulsed Laser Ablation in Liquid Nitrogen
Bibliographic record
Abstract
Molybdenum disulfide nanosheets (MoS 2 NSs) are synthesized via pulsed laser ablation of MoS 2 target in liquid nitrogen (LN 2 ) using the Q‐switched Nd:YAG (Nd:Y 3 Al 5 O 12 ) laser. Not only LN 2 facilitates the condensation of the laser‐induced plasma plume to produce MoS 2 NSs alongside main by‐products (namely, MoS 2 quantum dots (QDs)), but also provides an optimum condition for nitrogen‐doped MoS 2 (N‐MoS 2 ) synthesis as a p‐type semiconductor. The structural, optical, and chemical properties of NSs are investigated using various electron microscopic instruments and spectrometers. These attest to the formation of suspension MoS 2 NSs with a few‐layer structure and rather large lateral size. MoS 2 NSs enjoy extra chemical components such as Mo–N bonding. Furthermore, photoluminescence (PL) spectroscopy reveals exciton and trion peaks as the evidence of p‐type property. Subsequently, the Hall effect verifies the p‐type property of N‐MoS 2 NSs. By making use of the spin coating, the N‐MoS 2 diaphragm has been fabricated; then, it is mounted on the Fabry–Pérot interferometer (FPI) assembly using the fishing method. Thus, N‐MoS 2 in FPI acts as a sensitive component of the acoustic optical fiber sensor. The diaphragm operates as ultrasensitive membrane to detect acoustic waves enhancing the sensitivity up to 20% mainly due to the smaller Young's modulus.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".