Modeling of magnetic and magnetocaloric properties of polycrystalline La0.85Sr0.15Mn0.99Fe0.01O3 by a mean-field scaling method
Bibliographic record
Abstract
Magnetic and magnetocaloric properties of La0.85Sr0.15Mn0.99Fe0.01O3 perovskite oxides are investigated in the framework of the mean-field theory with a goal to develop a comprehensive model with parameters that can be used to optimize the caloric performances for cooling applications. Using the experimental magnetic isotherms M(H,T), we estimate and compare the exchange parameter (λ), the saturation magnetization (M0), the total angular momentum (J), and the gyromagnetic factor (g) for two different samples annealed at 1170 and 1250 °C. These parameters are used, in turn, in the simulation of the magnetic and the magnetocaloric properties of these La0.85Sr0.15Mn0.99Fe0.01O3 compounds assuming imperfect samples with compositional and/or magnetic inhomogeneities. For this purpose, a Gaussian distribution of the Curie temperature is assumed. The temperature dependence of the magnetic entropy change, −ΔSM(T), resulting from an applied field variation is simulated for both samples. The selected distribution captures the rounding of the −ΔSM(T) peak at its maximum and its broadening with growth conditions, features that are constantly observed in many bulk polycrystalline compounds.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".