Graded silicon based PECVD thin film for photovoltaic applications
Bibliographic record
Abstract
Silicon based thin film alloys are deposited using plasma enhanced chemical vapor deposition (PECVD) with silane, ammonia, and nitrous oxide as precursors with different partial pressure ratios. Numerous deposition conditions have been considered to produce films with a wide range of refractive indices. The optical properties of the films are mostly affected by hydrogen content and stoichiometry, which are characterized by means of Fourier Transform Infrared Spectroscopy (FTIR) and X-ray Photoelectron Spectroscopy (XPS) respectively. The results of spectroscopic ellipsometry measurement of the refractive index are correlated with stoichiometry extracted using XPS to enable the prediction of optical properties from process conditions. Based on the film characterization results, a graded index film is deposited to minimize the reflection loss. The optical properties of the film to be used as anti-reflection coating (ARC), i.e. the transmittance and reflectance, are measured using an optical spectrophotometer. In spite of the optical absorption in the high refractive index part of the film, it is shown that by employing a very thin layer of amorphous silicon, it is possible to reduce reflection below conventional graded index films consisting of silicon oxynitride, and still maintain the transmittance required for solar cell applications.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".