Transmission Electron Microscopy and Atomic Force Microscopy Observation of Air-Processed GdBa<sub>2</sub>Cu<sub>3</sub>O<sub>7-δ</sub> Superconductors Doped with Metal Oxide Nanoparticles (Metal = Zr, Zn, and Sn)
Bibliographic record
Abstract
Single-domain, c -axis-oriented 30-mm-diameter GdBa 2 Cu 3 O 7-δ (Gd123) melt-textured bulk superconductors have been successfully grown by the top-seeded melt growth method from precursors of Gd123, Gd 2 BaCuO 5 , and Ag 2 O in air with doping of nanosized ZrO 2 , ZnO, or SnO 2 . Transmission electron microscopy (TEM) unveils a large amount of BaZrO 3 or BaSnO 3 particles with an average diameter of approximately 50 nm respectively embedded in ZrO 2 or SnO 2 doped samples, while no Zn-rich nanoparticles are observed in the ZnO-doped samples. The critical temperature T c is almost unchanged up to a doping amount of 10 mol % for ZrO 2 - or SnO 2 -doped Gd123 melt-textured bulks, while ZnO-doped Gd123 becomes non-superconductive at this doping level. By atomic force microscopy (AFM), nanostripes with a wavelength of 15 nm are observed in the ZnO-doped Gd123 sample. Nanoscale particles in the grown Gd123 single domain, together with the micro-defects induced by nanoparticle doping, can account for the enhanced superconducting properties.
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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) | 0.002 | 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".