Conception, fabrication et caractérisation de transistors à effet de champ haute tension en carbure de silicium et de leur diode associée
Bibliographic record
Abstract
In the context of more electrical transports, mechanical devices tend to be replaced by their smaller electrical counterparts. However the device itself must support harsher environment and electrical constraints (high voltage, high temperature) thus making existing silicon devices inappropriate. Since the first Schottky diode commercialization in 2001, Silicon Carbide (SiC) is the favorite candidate for the fabrication of devices able to sustain high voltage with a high integration level. Thanks to its wide band gap energy and its high critical field, 4H-SiC allows the design of high voltage Junction Field Effect Transistor (JFET) with its antiparallel diode. Studied structures depends of many parameters, that need to be optimized. Since the influence of the variation of each parameter could not be isolated, we tried to find mathematical methods to emphase optimal values leading to set an optimization criterion. Thus, two main kinds of JFET structure were finely analyzed. In one hand, the aim of the structure that can sustain a voltage as high as possible leads to a complex fabrication process. In the other hand, the care of a simplification and a stabilization of manufacturing process leads to the design of simpler device, but with a bit less sustain capabilities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".