Tunable Optical Mode Ferromagnetic Resonance in FeCoB/Ru/FeCoB Synthetic Antiferromagnetic Trilayers under Uniaxial Magnetic Anisotropy
Bibliographic record
Abstract
Ferromagnetic resonance (FMR) is one of the most important characteristics of soft magnetic materials, which practically sets the maximum operation speed of these materials. There are two FMR modes in exchange coupled ferromagnet/nonmagnet/ferromagnet sandwich films. The acoustic mode has relatively lower frequency and is widely used in radio‐frequency/microwave devices, while the optical mode is largely neglected due to its tiny permeability even though it supports much higher frequency. Here, a realistic method is reported to enhance the permeability in the optical mode to an applicable level. FeCoB/Ru/FeCoB trilayers are carefully engineered with both uniaxial magnetic anisotropy and antiferromagnetic interlayer exchange coupling. This special magnetic structure exhibits a high optical mode frequency up to 11.28 GHz and a maximum permeability of 200 at resonance. An abnormally low inverse switch field (<200 Oe, less than 1/5 of the single layer) is observed which can effectively switch the system from optical mode with higher frequency into acoustic mode with lower frequency. The optical mode frequency and inverse switch field can be controlled by tailoring the interlayer coupling strengths and the uniaxial anisotropy fields, respectively. The tunable optical mode resonance thus can increase operation frequency while reduce operation field overhead in FMR based devices.
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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) | 0.000 | 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".