Investigation of the forward gate leakage current in pGaN/AlGaN/GaN HEMTs through TCAD simulations
Bibliographic record
Abstract
Abstract In this study, we examined the gate leakage characteristics of normally off pGaN/AlGaN/GaN HEMTs through a simulation study. The Fowler Nordheim Tunneling (FNT) mechanism mainly contributes to the gate leakage process as indicated by the Technology Computer-Aided Design (TCAD) simulation. However, at low bias, the FNT undercalculates the leakage current since the electric field is low in this region. This extra leakage current component at this low bias region can be attributed to the presence of surface traps. Trap-assisted tunneling current along with the FNT current can explain forward leakage characteristics of the pGaN HEMTs. Our TCAD simulations were matched with the experimental data for five devices from four different research groups to support this claim. Using TCAD simulations, we have been able to analyze several device parameters including the various potential drops inside the gate stack structure. We were able to identify some of the trap levels and compare them to the dominant defects expected to be present in the pGaN cap layer. Furthermore, we studied the effects of different device parameters on the gate leakage process in the pGaN HEMT.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".