Modulation of the photoluminescence spectrum by depth selective excitation of an embedded Si-nc layer
Bibliographic record
Abstract
Silicon nanocrystals (Si-nc) were produced by the implantation of Si + in excess into amorphous quartz and a 1 µm SiO 2 film thermally grown on an Si substrate. In the latter, the photoluminescence (PL) spectra from the Si-nc, induced by Ar + laser excitation, are modulated by Fabry–Perot type interference fringes due to the interference of the emitted light reflected at the Si/SiO 2 interface with that propagating directly towards the surface. In this paper, we investigate the spectral modulation and the PL as a function of the incidence angle of the pump laser and the Si + dose implantation. The modulation of the PL spectra is influenced by the distribution in depth of the pump laser intensity in the SiO 2 layer, the depth distribution of the Si-nc and the refractive index distribution of the layered structures. One goal of our work is to modulate the emission spectra by acting on the thickness of the SiO 2 layer. Simulations have been undertaken to establish a relation between the modulation of the PL spectrum and the depth distribution of both the pump laser intensity and the Si-nc. This study required the precise measurements of the depth distribution of both the complex refractive index ( n , k ) by ellipsometry and the Si-nc by transmission electron microscopy (TEM).
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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".