Device-Circuit Performance Analysis of a High-VT Recessed-p-Gate HEMT Employing Doped-Buried Layer
Bibliographic record
Abstract
Nowadays, one of the appealing choice of transistors for the next generation of high power devices is, AlGaN/GaN high-electron-mobility transistor (AlGaN/GaN-HEMT). Prior to now, numerous experiments were conducted utilizing various gate engineering techniques to propose high threshold voltage enhancement-mode HEMT architectures. In this paper, two new e-mode HEMT structures are proposed by taking motivation from our previously reported structure of Recessed p-GaN gate HEMT. By incorporating p-doped buried layer with recessed p-GaN gate in one HEMT structure, the threshold voltage is significantly increased. In first experiment, a p-doped GaN region is buried in to the Gallium Nitride (GaN) substrate of conventional p-GaN gate HEMT. In second experiment, a p-GaN buried layer is inserted in to GaN substrate of recessed p-GaN gate HEMT. V th of above 3V is obtained from the proposed structures, which is suitable to be implemented for high-frequency power switching applications. The proposed structures provides flexibility to tune V th and I d . The digital circuit compatibility is also tested by using both the proposed structures in a resistive-load inverter circuit. The transient analysis confirms that the HEMTs work properly in inverter circuit and the VTC analysis shows 98.5% of output voltage swing at input voltage of 5V. Highest NM H and NM L is measured as 2.85V and 2.65V respectively. The device simulation, calibration and circuit simulation is done in Silvaco TCAD software.
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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 | 0.001 | 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".