A micromagnetic investigation of magnetite grains in the form of Platonic polyhedra with surface roughness
Bibliographic record
Abstract
Micromagnetic calculations have been carried out for spherical magnetite particles with surface roughness consisting of patterns of conical bumps based on regular (Platonic) convex polyhedra. The purpose was to examine the effect of surface irregularities while avoiding overall shape anisotropy, which generally plays a dominant role in determining hysteresis properties. We considered three morphologies based on the tetrahedron (4 apices), the icosahedron (12 apices), and the dodecahedron (20 apices). Grains of three sizes were considered: 30 nm (single-domain, SD), 90 nm (on the single-domain/pseudo-single-domain boundary, SD/PSD), and 120 nm (stable pseudo-single-domain, PSD). We find that the morphologies investigated have very little effect on the hysteresis parameters of SD and marginal SD/PSD grains. However, in the PSD grains, coercivity increases significantly as bump amplitude increases from 0.1 to 0.9. This lends support to the long-standing notion that surface protuberances on larger grains are a possible source of paleomagnetically significant stable remanence, although the very high coercivities (on the order of 100 mT) observed in some rocks cannot be achieved. Classical Stoner-Wohlfarth shape anisotropy remains the only explanation for such ultra-stable remanence in magnetite-bearing rocks. This is confirmed by a specific example of a model “skeletal” grain consisting of three orthogonal parallelepipeds.
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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".