Wetting and spreading of Ca‐Y‐Ba‐Cu‐O solution on Y <sub>2</sub> O <sub>3</sub> and CaSZ crucible in growing Y <sub>1‐</sub> <i> <sub>x</sub> </i> Ca <i> <sub>x</sub> </i> Ba <sub>2</sub> Cu <sub>3</sub> O <sub>7‐δ</sub> single crystal
Bibliographic record
Abstract
Abstract Sizable and uniform Y 1‐ x Ca x Ba 2 Cu 3 O 7‐δ single crystals are of significant importance to study high‐temperature superconductivity. However, the severe liquid loss resulting from intrinsic wetting property during top‐seeded solution‐growth (TSSG), makes it difficult to obtain such crystals. Here the reactive wetting performance of the Ca‐Y‐Ba‐Cu‐O solution on two types of crucibles was studied. It was identified that the spreading process on the Y 2 O 3 crucible is characterized by forming double‐layer of Y 2 BaCuO 5 and YBa 2 Cu 3 O 7‐δ , while that on the CaSZ crucible (Ca‐stabilized ZrO 2 ) produces the BaZrO 3 layer with CuO phase. In the former case, the liquid has a low energy interface with the top layer of YBa 2 Cu 3 O 7‐δ , leading to strong spreading and creeping behaviors. Conversely, due to a high interfacial energy between solution and BaZrO 3 , the CaSZ crucible has a low wettability, particularly beneficial to solve the liquid loss problem. Consequently, with negligible liquid creeping out of CaSZ crucibles, we succeeded in growing a series of homogeneous Y 1‐x Ca x Ba 2 Cu 3 O 7‐δ single crystals with an acceptable size up to a × b × c = 11.2 × 11 × 4.8 mm 3 . Moreover the wetting modes of solution on various kinds of crucibles for TSSG in growing doped YBa 2 Cu 3 O 7‐δ single crystals were also elucidated. Most importantly, the understanding gained from this work is broadly applicable for producing other desirable doped‐crystals.
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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".