Influence of Material Properties on Ruggedness Evaluation of Package Architectures for SiC Power Devices
Bibliographic record
Abstract
Button shear tests at different temperatures between different mold compounds and Cu-leadframes have been performed to evaluate the adhesion of mold compounds to the inner surfaces of SiC-power devices. The results at different temperatures show the behavior of different material and layer stack combinations under storage at room temperatures as well as under operating conditions with elevated temperatures, where adhesion and thus the hermeticity of the device against moisture is significantly lowered. It has been shown that different thermomechanical properties of the mold compounds as well as the usage of different adhesion promoter materials have a significant effect on the adhesion properties of the mold compound to the leadframe surface of the SiC power devices, which have direct impact on the ruggedness and lifetime stability. Furthermore, these results have been correlated to thermomechanical simulations of the package architecture of SiC power devices under stress. Different wire bond architectures have been evaluated in simulations with and without die top delamination taken into account, showing that EMC delamination may play a major role in the lifetime stability of SiC power devices under thermomechanical stress like simulated in TCT- , IOL- and PTC-testing.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".