SiC Power MOSFETs – Status, Trends and Challenges
Bibliographic record
Abstract
SiC power MOSFETs are attractive electronic power switches for innovative power supply and motor drive solutions. The paper discusses this statement and specifies market segments offering the best chances for a commercialization. Due to well-known difficulties in achieving adequate channel conductivity, a lot of SiC-MOSFET publications focus on the channel mobility. However, for a power MOSFET this is only one important parameter affecting the performance. Other characteristics have to be considered too for an honest evaluation: transfer characteristics and blocking capability over the standard operation temperature range, handling of gate oxide stress and related reliability issues, capability of paralleling, dynamic stability, body diode characteristics, reproducibility of the fabrication process and device size. Various attempts have been made in recent years in order to address these features. Approaches differ in the use of different crystal orientations and polytypes, accumulation or inversion channel, implanted or epitaxially grown channels and novel oxidation techniques. Worldwide a trend to the planar DIMOS concept can be observed. Our present results are shown for a power SiC MOSFET designed for 10 A / 1200 V. Key data are a specific on-resistance of 12 m1cm2, the desired low but positive increase of the onresistance with temperature, static avalanche (20 mA DC @1574 V), short-circuit stability at 600 V for 20 9s and robust switching behavior.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".