Reverse‐Engineering Strain in Nanocrystallites by Tracking Trimerons
Bibliographic record
Abstract
Abstract Although strain underpins the behavior of many transition‐oxide‐based magnetic nanomaterials, it is elusive to quantify. Since the formation of orbital molecules is sensitive to strain, a metal–insulator transition should be a window into nanocrystallite strain. Using three sizes of differently strained Fe3O4 polycrystalline nanorods, the impact of strain on the Verwey transition and the associated formation and dissolution processes of quasiparticle trimerons is tracked. In 40 and 50 nm long nanorods, increasing isotropic strain results in Verwey transitions going from TV ≈ 60 K to 20 K. By contrast, 700 nm long nanorods with uniaxial strain along the (110) direction have TV ≈ 150 K—the highest value reported thus far. A metal–insulator transition, like TV in Fe3O4, can be used to determine the effective strain within nanocrystallites, thus providing new insights into nanoparticle properties and nanomagnetism.
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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".