Impact of Heat Treatments and Hole Density (p) on the Structural, Electrical, and Superconducting Properties of LnSrBaCu<sub>3</sub>O<sub>6+z</sub> (Ln = Eu, Sm, Nd) Compounds
Bibliographic record
Abstract
In this study, we thoroughly examined the impact of heat treatments and hole count (p) on the properties of LnSrBaCu3O6+z (Ln = Eu, Sm, Nd) compounds. We focused on preparation, X-ray diffraction with Rietveld refinement, AC susceptibility, DC resistivity measurements, and heat treatment effects. Two heat treatment types were applied: oxygen annealing [O] and argon annealing followed by oxygen annealing [AO]. As the rare earth Ln’s ionic radius increased, certain parameters notably changed. Specifically, c parameter, surface area S, and volume V increased, while critical temperature Tc and holes (p) in the CuO2 plane decreased. The evolution of these parameters with rare earth Ln’s ionic radius in [AO] heat treatment is linear. Regardless of the treatment, the structure is orthorhombic for Ln = Eu, tetragonal for Ln = Nd, orthorhombic for Ln = Sm [AO], and pseudo-tetragonal for Sm [O]. The highest critical temperature is reached with Ln = Eu (Tc [AO] = 87.1 K). Notably, for each sample, Tc [AO] surpasses Tc [O]. Observed data stems from factors including rare earth ionic size, improved cationic and oxygen chain order, holes count p in Cu(2)O2 planes, and in-phase purity of [AO] samples. Our research strives to clearly demonstrate that the density of holes (p) within the copper plane stands as a determinant impacting the structural, electrical, and superconducting properties of these samples. Meanwhile, the other aforementioned parameters contribute to shaping this density (p).
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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".