Morin transition in hematite: Size dependence and thermal hysteresis
Bibliographic record
Abstract
Hematite is a frequently used mineral in paleomagnetic and environmental magnetic studies. Just below room temperature, it undergoes a magnetic phase transition, the Morin transition, whose nature is an important part of our basic understanding of hematite's magnetism and magnetic memory. We have determined the temperature TM of the Morin transition from saturation remanence warming curves to be 250–261 K for 0.5–6 mm hematite natural single crystals, 257–260 K for 45–600 μm sieved crystal fractions, and 241–256 K for submicron synthetic hematites with grain sizes between 120 and 520 nm. The variation must be due to differences in crystal morphology, lattice strain, and crystal defects common in both synthetic and natural crystals. Our results are compatible with published data for 100 nm to 10 mm hematites and show that TM is nearly size independent, decreasing very gradually as particle size decreases over this broad range, which includes both multidomain (MD) and single‐domain (SD) structures. However, TM decreases sharply between 90 and 30 nm. Below 20 nm, the transition disappears entirely as near‐surface spins deviate strongly from the antiferromagnetic easy axis. Our SD and MD hematites exhibit a thermal hysteresis in the Morin transition: the values of TM in cooling and in heating are different. For the same cooling/warming rate, ΔTM is much greater for submicron hematites than for larger crystals. We attribute the lag in the transition in both cooling and heating to crystal imperfections and resulting internal stresses, and speculate that defects may serve to pin and stabilize surface spins. Preventing spin rotation in a region large enough to trigger the phase transition would inhibit destabilization of the weakly ferromagnetic phase in cooling and the antiferromagnetic phase in heating. The wide distribution of particle sizes in our submicron samples may also play a role.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".