Evidence of valence band perturbations in GaAsN/GaAs(001): Combined variable-angle spectroscopic ellipsometry and modulated photoreflectance investigation
Bibliographic record
Abstract
The contribution of the fundamental gap ${\text{E}}_{\ensuremath{-}}$ as well as those of the ${\text{E}}_{\ensuremath{-}}+{\ensuremath{\Delta}}_{\text{so}}$ and ${\text{E}}_{+}$ transitions to the dielectric function of ${\text{GaAs}}_{1\ensuremath{-}x}{\text{N}}_{x}(001)$ alloys were determined from variable-angle spectroscopic ellipsometry and modulated photoreflectance spectroscopy analyses. The oscillator strength of the ${\text{E}}_{\ensuremath{-}}$ optical transition increases weakly with nitrogen incorporation. The two experimental techniques independently reveal that the oscillator strength of the ${\text{E}}_{\ensuremath{-}}+{\ensuremath{\Delta}}_{\text{so}}$ transition becomes larger compared to that of the fundamental gap as the N content increases. Since the same conduction band is involved in both the ${\text{E}}_{\ensuremath{-}}$ transition and its split-off replica ${\text{E}}_{\ensuremath{-}}+{\ensuremath{\Delta}}_{\text{so}}$, this result reveals that adding nitrogen in ${\text{GaAs}}_{1\ensuremath{-}x}{\text{N}}_{x}(001)$ alloys affects not only the conduction but also the valence bands.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".