Oxygen-based digital etching of AlGaN/GaN structures with AlN as etch-stop layers
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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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) | 0.000 | 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 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".