Influence of Substrate Preparation and Epitaxial Growth Parameters on the Dislocation Densities in 4H-SiC Epitaxial Layers
Bibliographic record
Abstract
Basal Plane Dislocations (BPD) in SiC are thought to cause degradation of bipolar devices as they can trigger the formation and expansion of stacking faults during device operation. Therefore, epilayers without any BPD are strongly recommended for the achievement of long-term reliable bipolar devices. Such epilayers can be achieved by supporting the conversion of BPD into Threading Dislocations (TD), which depends on the epitaxial growth mode (as described in literature). In this work, the influence of several pre-treatments of the SiC substrate prior to epitaxial growth and different epitaxial growth parameters on the reduction of the BPDs in the SiC epilayers was investigated on 4° off-axis substrates. The dislocation content in substrates and epilayers was determined by Defect Selective Etching (DSE) in molten KOH. The averaged BPD density in epitaxial layers can be reduced to < 100 cm-2 for substrate preparation techniques and to < 30 cm-2 for well-suited epitaxial growth parameters. A certain combination of epitaxial growth parameters leads to < 3 BPD/cm2 in the epitaxial layer.
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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".