New barrier layer design for the fabrication of gallium nitride-metal-insulator-semiconductor-high electron mobility transistor normally-off transistor
Bibliographic record
Abstract
Abstract This paper reports on the fabrication of an enhancement-mode AlGaN/GaN metal-insulator-semiconductor-high electron mobility transistor with a new barrier epi-layer design based on double Al0.2Ga0.8N barrier layers separated by a thin GaN layer. Normally-off transistors are achieved with good performances by using digital etching (DE) process for the gate recess. The gate insulator is deposited using two technics: plasma enhance chemical vapour deposition (sample A) and atomic layer deposition (sample B). Indeed, the two devices present a threshold voltage (V th) of +0.4 V and +0.9 V respectively with ΔV th about 0.1 V and 0.05 V extracted from the hysteresis gate capacitance measurement, a gate leakage current below 2 × 10−10 A mm−1, an I ON/I OFF about 108 and a breakdown voltage of V BR = 150 V and 200 V respectively with 1.5 µm thick buffer layer. All these results are indicating a good barrier surface quality after the gate recess. The DE mechanism is based on chemical dissolution of oxides formed during the first step of DE. Consequently, the process is relatively soft with very low induced physical damages at the barrier layer surface.
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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 | 0.001 | 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".