Modeling Bias Dependence of Self-Heating in GaN HEMTs Using Two Heat Sources
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Bibliographic record
Abstract
This article proposes a new approach for modeling self-heating in gallium nitride (GaN) high-electron-mobility transistors (HEMTs). The proposed approach utilizes two heat sources to model the effects of the relatively uniform heat generation when the device is in the linear regime and the concentrated heat generation in the high-field area after the device pinches off. Compared to traditional single heat source modeling approaches, the proposed approach yields a model that can accurately capture the bias dependence of the heat and temperature distribution in the GaN HEMT channel without resorting to the more resource-intensive electrothermal simulations. It also leads to a simple yet accurate analytical expression for the maximum channel temperature using thermal resistances that have clear geometric dependence.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it