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Record W4402509303 · doi:10.1109/lmag.2024.3461575

Role of Shape Ellipticity on Dipole-Exchange Spin Waves in Ferromagnetic Nanorings

2024· article· en· W4402509303 on OpenAlexaff
Yassin Elmeligi, Bushra Hussain, M. G. Cottam

Bibliographic record

VenueIEEE Magnetics Letters · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsWestern University
Fundersnot available
KeywordsFerromagnetismCondensed matter physicsSpin waveMagnetic dipoleSpin polarizationSpin (aerodynamics)DipoleMagnetic domainPhysicsMaterials scienceMagnetizationMagnetic fieldQuantum mechanicsElectron

Abstract

fetched live from OpenAlex

The properties of the quantized spin-wave frequencies and the transition field between the two stable magnetization states (the low-field vortex state and the higher-field onion state) are studied for elliptical nanorings. The dependences of these quantities on the nanoring sizes and the degree of ellipticity are examined over a wide range of values for the applied magnetic field and its orientation. The novel effects introduced when the symmetry axes of the inner elliptical edges of the rings are rotated relative to those of the outer elliptical edge are also studied. To characterize these effects, our theory makes use of a Hamiltonian-based dipole-exchange methodology, adapted from that used to elucidate the spin-wave modes in circular nanorings. It is found that spin-wave frequencies and the behavior of the transition field(s) depend sensitively on the degree of ellipticity, the rotation angle of the inner elliptical edge with respect to the outer elliptical edge, and the direction of the applied field relative to the nanoring axes.

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)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.221
Teacher spread0.212 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueIEEE Magnetics LettersSame topicMagnetic properties of thin filmsFrench-language works237,207