Harmonic Resonance Enhanced Second-Harmonic Generation in the Monolayer WS<sub>2</sub>–Ag Nanocavity
Bibliographic record
Abstract
The enhanced second-harmonic generation (SHG) from a monolayer WS 2 coupled to a plasmonic nanocavity is experimentally and theoretically investigated. The nanocavity is comprised of monodispersed Ag nanocubes separated from an Ag film by a spacer Al 2 O 3, namely, the nanoparticle on mirror (NPoM) system. When the surface plasmon polariton resonance (SPPR) wavelength of NPoM nanocavity overlaps well with the SHG wavelength of the monolayer WS 2 (namely, harmonic resonance), a ∼300-fold SHG enhancement is achieved in experiment. For theoretical understanding, the quantum mechanical density matrix method has been used to develop a theory for SHG. It is found that the SHG intensity of nanohybrid is proportional to the square of the local-field intensity in NPoM nanocavity at SHG wavelength, which is ascribed to the dipole–quadrupole interaction between dipole, P SHG, in the monolayer WS 2 and quadrupole, Q Ag, in Ag nanocavity. It is significantly different from that in metal nanoparticles under harmonic resonance, which is proportional to the local-field intensity. Therefore, it provides a novel mechanism for enhancing SHG signals from metal–semiconductor nanohybrids, which has potential applications in nonlinear devices and hybrid nonlinear metasurfaces.
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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".