The Experimentalist's Guide to the Cycloid, or Noncollinear Antiferromagnetism in Epitaxial BiFeO<sub>3</sub>
Bibliographic record
Abstract
Abstract Bismuth ferrite (BiFeO 3 ) is one of the most widely studied multiferroics. The coexistence of ferroelectricity and antiferromagnetism in this compound has driven an intense search for electric‐field control of the magnetic order. Such efforts require a complete understanding of the various exchange interactions that underpin the magnetic behavior. An important characteristic of BiFeO 3 is its noncollinear magnetic order; namely, a long‐period incommensurate spin cycloid. Here, the progress in understanding this fascinating aspect of BiFeO 3 is reviewed, with a focus on epitaxial films. The advances made in developing the theory used to capture the complexities of the cycloid are first chronicled, followed by a description of the various experimental techniques employed to probe the magnetic order. To help the reader fully grasp the nuances associated with thin films, a detailed description of the spin cycloid in the bulk is provided. The effects of various perturbations on the cycloid are then described: magnetic and electric fields, doping, epitaxial strain, finite size effects, and temperature. To conclude, an outlook on possible device applications exploiting noncollinear magnetism in BiFeO 3 films is presented. It is hoped that this work will act as a comprehensive experimentalist's guide to the spin cycloid in BiFeO 3 thin films.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".