Optical index profile of nonuniform depth-distributed silicon nanocrystals within SiO2
Bibliographic record
Abstract
Optical properties of silicon nanocrystals (Si-ncs) prepared by silicon implantation into silicon oxide have been investigated by photoluminescence measurements and spectroscopic ellipsometry. The dielectric function associated with Si-nc uniformly and nonuniformly depth distributed has been determined by means of the Tauc–Lorentz (TL) model, using the Bruggemann effective medium approximation. The evolution of the Si-nc sublayer dielectric response as a function of the ion fluence has been established for volume fractions of Si excess varying between 9.1% and 50.4%. Comparison between the depth profile of optical indices determined by ellipsometry and TRIM calculations shows that for implanted Si volume fraction lower than 30%, the center and the width of the optical index profile agree with the spatial distribution of the implanted Si when both the swelling and the ion sputtering effects are taken into account. This is also valid in systems having two separate Si-nc sublayers, where the geometric characterization of the optical index variations has been computed from a data extrapolation. For a volume fraction of 50.4%, where the ion implantation performed at high fluence can activate the oxygen depletion from the material surface, the spatial distribution of the optical refractive index is deeper and narrower than the Si excess profile.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".