Ellipsometric Characterization on Multi-Layered Thin Film Systems during Hydrogenation
Bibliographic record
Abstract
Ellipsometric characterization on the basis of multi-layered modeling is proposed to describe the optical and electrical property transients of hydrogenated films. In particular, two-step modeling is developed to make ellipsometric characterization on the yttrium film and the palladium capped yttrium film deposited on the SiO2 glass substrate. In the former, Y2O3 film deposited on SiO2 substrate is prepared to estimate the dielectric response of yttrium oxide layer as the first step. These data are further utilized in the second step to determine optical and electric properties of yttrium-base multi-layers which are composed of metallic yttrium, composite of metallic yttrium and Y2O3, and Y2O3 layer with surface roughness. In the latter, a palladium film deposited on SiO2 substrate is prepared to investigate the dielectric response of palladium hydrides. The estimated dispersion functions are further used in the multi-layered modeling for hydrogenated Pd-capped yttrium films on the SiO2 substrate. Under the ambient hydrogen pressure, palladium coated yttrium films have low resistivity and hydrogenated yttrium is still metallic. This palladium coating works as a top capping layer for yttrium film during hydrogenation and de-hydrogenation.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".