Initial results for epitaxial growth of InN on gallium oxide and improved Migration-Enhanced Afterglow Epitaxy growth on gallium nitride
Bibliographic record
Abstract
In this paper, the authors report on epitaxial thin InN layers grown on commercially available undoped GaN buffer layers and on Ga2O3 interlayers produced by Migration-Enhanced Afterglow Epitaxy (MEAglow). The InN layers reported here, also grown by the MEAglow technique, are 100–200 nm thick and have a measured absorption edge between 1.3 and 1.95 eV. Advancements in the growth process have now allowed the authors to improve the InN layers so that the growth has excellent two-dimensional morphology. Scanning electron microscope images show that terracing is strongly evident for samples grown on GaN templates. Atomic force microscopy shows a maximum height of the steps of about 2 nm. For the samples grown on Ga2O3, crystal quality is superior to InN grown on AlN buffers with similar thicknesses. X-ray diffraction ω-2θ measurements indicate a full width of half maximum (FWHM) of 342–389 arcseconds for these extremely thin layers; a good part of this x-ray diffraction FWHM is likely due to residual strain between the InN and GaN or between the InN and oxide.
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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".