Role of ZrO<sub>2</sub>/SnO<sub>2</sub> Nano-Particles on Superconducting Properties and Microstructure of Melt-Processed Gd123 Superconductors
Bibliographic record
Abstract
Bulk GdBa2Cu3O7–δ(Gd123) superconductors were fabricated in air by adding ZrO2/SnO2nanoparticles with an average size of 50 nm. The effect of addition on microstructure and superconducting properties was investigated by scanning electron microscopy (SEM)/transmission electron microscopy (TEM) and SQUID. SEM results show that the distribution of Gd2BaCuO5(Gd211) particles is inhomogeneous around the seeding site of single domain, induced by the addition of nano-par-ticles. Particles with size less than 50 nm were observed by TEM inside Gd123 single domain, while the typical size of fined Gd211 particles is about 100 nm. Critical current density (Jc) was enhanced by the proper amount addition of ZrO2/SnO2additions. The highestJcof 100,000 A/cm2was presently achieved in the bulk with 0.4 mol % ZrO2, under self-field at 77 K. Excess amount addition rather suppresses superconducting properties. The optimum addition amount is 0.2-0.8 mol % for ZrO2and 0.4-0.8 mol % for SnO2, ratio to Gd123, respectively.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".