Effect of Uniaxial Anisotropy and Demagnetizing Effects on the Magnetic Behavior of Polycrystalline Gadolinium
Bibliographic record
Abstract
Gadolinium (Gd) is a soft ferromagnetic material with uniaxial magnetic anisotropy. The anisotropy is responsible for some magnetic features that are quite different from those observed in most common ferromagnetic materials. Polycrystalline Gd exhibits thermal hysteresis in which the memory of past magnetic history is stored in the buildup of magnetic charge density around grain boundaries on cooling in magnetic fields from above the spin-reorientation temperature T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SR</sub> ~ 235 K, in the range where the uniaxial anisotropy is positive. This has the effect of narrowing domain walls (DWs) that interact more strongly with defects, such as grain boundaries. Below T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SR</sub> , where the negative uniaxial anisotropy is increasing in magnitude with decreasing T, the magnetic susceptibility increases by orders of magnitude. Negative uniaxial anisotropy makes it easier for DWs to move past defects, such as grain boundaries, because wider Néel walls are favored over narrower Bloch walls. Magneto-thermal measurement protocols are used to study the effect of cooling in a field μ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> H = -50 mT to 5 K and then measuring at lower constant fields, typically μ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> H = 3.5 mT, from 5 to 380 K. The protocols permit the extraction of the temperature dependencies of the susceptibility, which depends on anisotropy, and of the frozen fraction of the magnetization, which consists of two parts. One part freezes upon field cooling below T = 100 K, and a harder one freezes above 250 K. On first warming, the former unfreezes below 100 K, while the latter unfreezes above 250 K.
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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 | 0.001 |
| 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 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".