Oxygen-based digital etching of AlGaN/GaN structures with AlN as etch-stop layers
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Bibliographic record
Abstract
O2 plasma-based digital etching of Al0.25Ga0.75N with a 0.8 nm AlN spacer on GaN was investigated using an inductively coupled plasma etcher. Silicon oxide layer was used as the hard mask. At 40 W RF bias power and 40 sccm oxygen flow, the etch depth of Al0.25Ga0.75N was 5.7 nm per cycle. The 0.8 nm AlN spacer layer acted as an etch-stop layer in three cycles. The surface roughness improved from 0.66 to 0.33 nm after the three and seven digital etch cycles. Compared to the dry etch only approach, this technique smoothed the surface instead of causing surface roughening. Compared to the selective thermal oxidation with a wet etch approach, this method is less demanding on the epitaxial growth and saves the oxidation process. It was shown to be effective in precisely controlling the AlGaN etch depth required for recessed-AlGaN HEMTs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it