Model for temperature-dependent magnetization of nanocrystalline materials
Bibliographic record
Abstract
A magnetization model of nanocrystalline materials incorporating intragrain anisotropies, intergrain interactions, and texture effects has been extended to include the thermal fluctuations. The method relies on the stochastic Landau–Lifshitz–Gilbert theory of magnetization dynamics and permits to study the magnetic properties of nanocrystalline materials at arbitrary temperature below the Currie temperature. The model has been used to determine the intergrain exchange constant and grain boundary anisotropy constant of nanocrystalline Ni at 100 K and 298 K. It is found that the thermal fluctuations suppress the strength of the intergrain exchange coupling and also reduce the grain boundary anisotropy. In comparison with its value at 2 K, the interparticle exchange constant decreases by 16% and 42% and the grain boundary anisotropy constant decreases by 28% and 40% at 100 K and 298 K, respectively. An application of the model to study the grain size-dependent magnetization indicates that when the thermal activation energy is comparable to the free energy of grains, the decrease in the grain size leads to the decrease in the magnetic permeability and saturation magnetization. The mechanism by which the grain size influences the magnetic properties of nc–Ni is discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".