NMR Studies of Nitrogen Doping in the 4H Polytype of Silicon Carbide: Site Assignments and Spin−Lattice Relaxation
Bibliographic record
Abstract
Nitrogen doping in silicon carbide converts an insulator to a wide-band gap semiconductor with many potential uses. Most doping studies have involved the 4H and 6H polytypes, which alone among the many known hexagonal SiC polytypes are commercially available as large single crystals. Nitrogen doping makes 13 C and 29 Si NMR spin−lattice relaxation much more efficient, presumably by donating unpaired electron density to the conduction band. However the effect is site-specific. We now report a huge site-specific difference in relaxation efficiency, a factor of 60, between the two carbon sites in the 4H polytype. Because the relaxation of the undoped material is extremely slow, such measurements provide a very sensitive probe of differences in local electronic structure at the sites. The crystallographic sites differ only in their next-nearest neighbors because the first neighbors are always tetrahedral, and the only difference between the fast- and slow-relaxing carbon sites, out to the second-neighbor positions, is a rotation through 60° of three of the second-neighbor atoms. We have previously reported similar but less extreme site-specific differences in 13 C relaxation behavior in the 6H polytype. Interpretation of these results requires firm assignments of the 13 C and 29 Si signals in both polytypes to the specific crystallographic sites: three in the 6H and two in the 4H polytype. This has been problematic because all peaks have equal intensities in both polytypes. We propose new peak assignments, correcting the different literature reports. The new assignments are based on a combination of electronic structure calculations, 13 C-to- 29 Si cross-polarization experiments, and chemical shift anisotropy studies.
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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 | 0.000 |
| 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 | 0.000 |
| 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".