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Record W2061400996 · doi:10.1142/s0218625x08011949

DIPOLE-EXCHANGE SPIN WAVES IN FERROMAGNETIC NANOSTRUCTURES WITH SPHERICAL GEOMETRIES

2008· article· en· W2061400996 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSurface Review and Letters · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsWestern University
Fundersnot available
KeywordsCondensed matter physicsDipoleSPHERESFerromagnetismSpin wavePermalloyPhysicsNanostructureHamiltonian (control theory)Magnetic fieldMolecular physicsRADIUSMaterials scienceMagnetizationQuantum mechanics

Abstract

fetched live from OpenAlex

Dipole–exchange spin waves (SWs) are studied in ferromagnetic nanostructures with spherical geometries such as spheres, part spheres, and spherical shells, both individually and in finite-sized arrays. A microscopic theory is used based on a spin Hamiltonian, which incorporates the short-range exchange and long-range magnetic dipole–dipole interactions, as well as an external magnetic field applied in any direction. Our theory is advantageous for describing the dynamical properties of inhomogeneously magnetized samples, and the use of phenomenological boundary conditions is avoided. Numerical results are deduced for the frequencies of the discrete SW modes and their dependence on the radius, spacing between particles, applied field, etc. Applications are made to Permalloy Fe 19 Ni 81 and alloy Co 80 Ni 20 nanoparticles with their sizes varying from 10 to 100 nm. Through a Green function theory, the spatial distributions and spectral intensities of the SWs are also deduced. The mode-mixing (hybridization) effects on the SW branches are found to be important, depending on the particle sizes and geometries.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 head0.010
GPT teacher head0.216
Teacher spread0.206 · 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