Ferromagnetic resonance force spectroscopy of individual sub-micron size samples
Bibliographic record
Abstract
We review how a magnetic resonance force microscope (MRFM) can be applied to perform ferromagnetic resonance (FMR) spectroscopy of \emph{individual} sub-micron size samples. We restrict our attention to a thorough study of the spin-wave eigen-modes excited in permalloy (Py) disks patterned out of the same 43.3 nm thin film. The disks have a diameter of either 1.0 or $0.5 μ$m and are quasi-saturated by a perpendicularly applied magnetic field. It is shown that \emph{quantitative} spectroscopic information can be extracted from the MRFM measurements. In particular, the data are extensively compared with complementary approximate models of the dynamical susceptibility: i) a 2D analytical model, which assumes an homogeneous magnetization dynamics along the thickness and ii) a full 3D micromagnetic simulation, which assumes an homogeneous magnetization dynamics below a characteristic length scale $c$ and which approximates the cylindrical sample volume by a discretized representation with regular cubic mesh of lateral size $c=3.9$ nm. In our analysis, the distortions due to a breaking of the axial symmetry are taken into account, both models incorporating the possibility of a small misalignment between the applied field and the normal of the disks.
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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 | 0.001 | 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".