Buried superconducting layers comprised of magnesium diboride nanocrystals formed by ion implantation
Bibliographic record
Abstract
Superconducting layers of MgB2 were formed on Si substrates using techniques that are widely used and accepted in the semiconductor industry. Mg ions were implanted into boron films deposited on Si or Al2O3 substrates. After a thermal processing step, buried superconducting layers comprised of MgB2 nanocrystals were obtained which exhibit the highest Tc reported so far for MgB2 on silicon (Tconset≈33.6 K, ΔTc=0.5 K, as measured by current transport). These results show that our approach is clearly applicable to the fabrication of superconducting devices that can be operated at much higher temperatures (≈20 K) than the current Nb technology (≈6 K) while their integration with silicon structures remains straight-forward.
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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 | 0.000 |
| 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) | 0.000 | 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".