A Novel Oxygen-Based Digital Etching Technique for p-GaN/AlGaN Structures without Etch-Stop Layers*
Bibliographic record
Abstract
A novel O2 plasma-based digital etching technology for p-GaN/AlGaN structures without any etch-stop layer was investigated using an inductively coupled plasma (ICP) etcher, with 100 W ICP power and 40 W rf bias power. Under 40 sccm O2 flow and 3 min oxidation time, the p-GaN etch depth was 3.62 nm per circle. The surface roughness improved from 0.499 to 0.452 nm after digital etching, meaning that no observable damages were caused by this process. Compared to the dry etch only methods with Cl2/Ar/O2 or BCl3/SF6 plasma, this technique smoothed the surface and could efficiently control the etch depth due to its self-limiting characteristic. Furthermore, compared to other digital etching processes with an etch-stop layer, this approach was performed using ICP etcher and less demanding on the epitaxial growth. It was proved to be effective in precisely controlling p-GaN etch depth and surface damages required for high performance p-GaN gate high electron mobility transistors.
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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".