Investigation of the High-Temperature Operation of AlGaN/GaN HFETs via Studying the Impact of Temperature Dependency of Drift Transport Characteristics
Bibliographic record
Abstract
Investigation of the reliable operation of AlGaN/GaN HFETs at elevated temperatures is attempted. In this paper, a Monte Carlo-based temperature-dependent mobility model, with incorporation of steady-state velocity overshoot, is employed in modeling the drain current-voltage characteristics of AlGaN/GaN HFETs at 300, 400, and 500 K. One of the major merits of this model is that it employs a very small set of fitting parameters. The modeled drain current-voltage characteristics have been successfully matched to the experimental characteristics at the aforementioned temperatures. While confirming that a brief measurement at these temperatures is of no reliability concern on the quality of the metal-semiconductor contacts, this matching proves that the temperature dependency of the electron drift velocity is the cause of the degradation of drain current within the aforementioned range of temperature. In producing the aforementioned match for the long-gate AlGaN/GaN HFETs, it is also shown that the accurate modeling of the temperature dependency of the low-field drift transport is more consequential than the accurate representation of the transport in the medium-to-high electric fields.
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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 | 0.001 |
| 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".