SiC Power Devices: Product Improvement Using Diffusion Soldering
Bibliographic record
Abstract
SiC power devices have reached a high market penetration, especially for high-voltage applications like switch mode power supplies. In the past, however, the superior material properties like, e.g., good thermal conductivity, have often not been put to full use due to the limitations of current packaging techniques. Especially the inferior thermal conductivity of current die attach materials have been an obstacle to realise the full potential of SiC technologies. In this paper, we describe in detail the use of diffusion solder for the die attach of SiC chips. Replacing the conventional solder layer by a thin metal stack for diffusion soldering, the thermal conductivity of the device is significantly improved. In addition, we show the positive impact of diffusion soldering on the assembly process and on the device reliability. These results are interesting for, both, SiC diodes and switches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".