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Record W2079279246 · doi:10.1142/s0218625x07009505

MAGNETOSTATIC MODES IN NANOMETER-SIZED FERROMAGNETIC AND ANTIFERROMAGNETIC TUBES

2007· article· en· W2079279246 on OpenAlexaff
Tushar Kanti Das, M. G. Cottam

Bibliographic record

VenueSurface Review and Letters · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsWestern University
Fundersnot available
KeywordsCondensed matter physicsAntiferromagnetismFerromagnetismPhysicsSpin waveMagnetic fieldDipoleRADIUSFerromagnetic resonanceMagnetic dipoleBoundary value problemMagnetizationQuantum mechanics

Abstract

fetched live from OpenAlex

A theory is presented for the magnetostatic modes in ferromagnetic and antiferromagnetic nanotubes, which have a large length-to-radius aspect ratio and an external magnetic field parallel to the cylindrical axis. The surface and bulk magnetic excitations (or magnetostatic spin waves) are studied for cases where the dipole–dipole interactions are dominant in the spin dynamics. This situation can be realized at sufficiently small wavevectors by inelastic light scattering or magnetic resonance techniques. A macroscopic continuum theory is developed, using the magnetostatic form of Maxwell's equations and the electromagnetic boundary conditions, and the characteristic equations (or dispersion relations) are deduced for the magnetostatic modes. Numerical calculations are presented for ferromagnetic and antiferromagnetic nanostructures, taking Ni 80 Fe 20 and MnF 2, respectively. The spatial variations of the mode amplitudes are also investigated.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.232
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2007
Admission routes1
Has abstractyes

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