Influence of Deposition Conditions on the Characteristics of Luminescent Silicon Carbonitride Thin Films
Bibliographic record
Abstract
The influence of the substrate temperature and argon gas flow on the compositional, structural, optical, and light emission properties of amorphous hydrogenated silicon carbonitride (a-SiC x N y :H) thin films were studied. Thin films were fabricated using electron cyclotron resonance plasma enhanced chemical vapor deposition (ECR PECVD) at a range of substrate temperatures from 120 to 170°C (corresponding to deposition temperatures of 300 to 450°C) in a mixture of SiH 4 , N 2 , and CH 4 precursors. Variable angle spectroscopic ellipsometer (VASE), elastic recoil detection (ERD), and Rutherford backscattering spectrometry (RBS) verified optical bandgap widening, layer densification, and an increase of the refractive index at higher substrate temperatures. The microstructure of a-SiC x N y :H z thin films was determined by X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared (FTIR) spectroscopy. The substrate temperature strongly affected the binding state of all atoms, and in particular, carbon atoms attached to silicon and nitrogen, as well as hydrogen-terminated bonds. We correlated the films' microstructural changes to a higher species' mobility arriving on the growin layer at higher temperatures. Photoluminescence (PL) measurements showed that the total intensity of visible light emission increased. A systematic blueshift of the centroid of the wide PL peak was observed following the increase of optical gap.
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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".