An x-ray diffraction and Raman spectroscopic analysis of thin-films of silicon grown by ultrahigh-vacuum evaporation and the thin-film silicon continuum
Bibliographic record
Abstract
The analysis presented herein draws upon a reservoir of experimental data that has been harvested from experiments performed on a collection of ultrahigh-vacuum evaporation prepared thin silicon film samples. A molecular beam epitaxy deposition setup was commissioned for the film preparations, these growths being performed for different growth temperatures and substrate selections. Grazing incidence x-ray diffraction and Raman spectroscopic measurements probed each thin silicon film’s microstructure. From the diffraction patterns, through applying Scherrer’s equation, the crystallite dimensions’ dependence on the growth temperature is resolved for each considered substrate selection; these results are confirmed through determinations of the crystallite dimensions through an evaluation of the relevant Raman spectral shifts. From the ensemble of Raman spectra that is available, drawing upon a recently developed Raman spectral processing protocol, full spectral decompositions are pursued. From these decompositions, the location, width, and character of each identified peak are noted, and the evolution of these decompositions in response to growth temperature variations is examined for the different substrate selections. Finally, an interpretation and a discussion about the results are presented, with the concept of thin-film silicon being on a continuum providing the framework for some aspects of this analysis.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".