Influence of Heating and Cooling Rates of Post-Implantation Annealing Process on Al-Implanted 4H-SiC Epitaxial Samples
Bibliographic record
Abstract
We report on topographical, structural and electrical measurements of aluminum-implanted and annealed 4H-SiC epitaxial samples. The influence of heating-up and cooling-down temperature rates on the SiC surface roughness, the crystal volume reordering and the dopant electrical activation was particularly studied. A higher heating-rate was found to preserve the rms roughness for annealing temperatures lower than 1700°C, and to improve the sheet resistance whatever the annealing temperature due to a better dopant activation (except for 1600°C process, which induced a dark zone in the sample volume). A complete activation was calculated for an annealing at 1700°C during 30 minutes, with a ramp-up at 20°C/s. Rising the cooling-down rate appeared to increase the sheet resistance, probably due to a higher concentration of point defects in the implanted layer.
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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 | 0.001 |
| 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) | 0.000 | 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".