Smooth wet etching by ultraviolet-assisted photoetching and its application to the fabrication of AlGaN/GaN heterostructure field-effect transistors
Bibliographic record
Abstract
We characterize a KOH-based ultraviolet (UV) photoassisted wet etching technique using K2S2O8 as the oxidizing agent. The solution provides a well-controlled etch rate and produces smooth high-quality etched surfaces with a minimal degradation in surface roughness as measured by atomic force microscopy. The evolution of the solution pH upon exposure to UV radiation is identified as key to obtaining smooth etched surfaces and a controlled etch rate: Unless steps are taken to maintain the pH above 12.0, the etch rate displays a sharp drop that coincides with a gross roughening of the etched surface. The applicability of the present technique is demonstrated by the fabrication of high-quality mesa-isolated AlGaN/GaN hetrostructure field-effect transistors. In addition, the etch presented here features a high selectivity to C-doped layers which should prove useful in the fabrication of AlGaN/GaN hetrostructure bipolar transistors. The method is well adapted to device processing applications because it does not require connection to the sample to an external electrochemical cell.
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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".