Large-Area Homoepitaxial Growth of Low-Doped Thick Epilayers for Power Devices with V<sub>BR</sub> > 4 kV
Bibliographic record
Abstract
In this paper we present results on the growth of low-doped thick epitaxial layers on 4° off-oriented 4H-SiC using a commercially available hot-wall multi-wafer CVD system. For the first time we show results of a low-doped full-loaded 73” run on 4° off-oriented substrates with a layer thickness of more than 70 µm. The target doping concentration of 1.2×1015 cm-3 is suitable for blocking voltages > 6 kV. Results on doping, thickness and wafer-to-wafer homogeneities are shown. The surface quality of the grown layers was characterized by AFM. The density of different types of dislocations was determined by Defect Selective Etching.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".