Circuit Techniques in GaN Technology for High-Temperature Environments
Bibliographic record
Abstract
As a wide bandgap semiconductor, Gallium Nitride (GaN) device proves itself as a suitable candidate to implement high temperature (HT) integrated circuits. GaN500 is a technology available from the National Research Council of Canada to serve RF applications. However, this technology has the potential to boost HT electronics to higher ranges of operating temperatures and to higher levels of integration. This paper summarizes the outcome of five years of research investigating the implementation of GaN500-based circuits to support HT applications such as aerospace missions and deep earth drilling. More than 15 integrated circuits were implemented and tested. We performed the HT characterization of passive elements integrated in GaN500 including resistors, capacitors, and inductors up to 600 °C. Moreover, we developed for the first time several digital circuits based on GaN500 technology, including logic gates (NOT, NAND, NOR), ring oscillators, D Flip-Flop, Delay circuits, and voltage reference circuits. The tested circuits are fabricated on a 4 mm × 4 mm chip to validate their functionality over a wide range of temperatures. The logic gates show functionality at HT over 400 °C, while the voltage reference circuits remain stable up to 550 °C.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".