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Record W7101825450 · doi:10.3390/appliedphys1020006

Role of Interfacial Dzyaloshinskii–Moriya Interactions on Dipole-Exchange Spin Waves in Finite-Width Ferromagnetic Nanostripes

2025· article· en· W7101825450 on OpenAlexaff

Bibliographic record

VenueAppliedPhys · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Ecology and Taxonomy Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsFerromagnetismSpin waveAntisymmetric relationAmplitudeMagnetizationZeeman effectDispersion (optics)Dispersion relationMagnetic field

Abstract

fetched live from OpenAlex

In this paper, we explore the magnetization dynamics in a long ferromagnetic nanostripe with finite width in the presence of antisymmetric Dzyaloshinskii–Moriya exchange interactions (DMIs). It is known that DMIs, which are currently of great interest because they give rise to chiral and nonreciprocal properties and influence surface topologies, can be enhanced by interfacing the nanostripe with a heavy metal. Our theoretical approach employs a microscopic (or Hamiltonian-based) analysis that includes symmetric bilinear exchange, antisymmetric DMI, long-range dipole–dipole interactions, and Zeeman energy due to an external magnetic field applied out of the plane of the nanostripe. In this geometry, we calculate the frequencies and amplitudes of the discrete spin-wave modes that have a standing-wave character across the finite width of the stripe and a propagating character (with wavenumber k) along the stripe length. The individual spin-wave modes display nonreciprocal propagation in their dispersion relations due to DMI. We also find that there may be localized edge spin waves with amplitudes that undergo spatial decay near the stripe edges.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.454

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)0.0000.000

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 head0.013
GPT teacher head0.223
Teacher spread0.210 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2025
Admission routes1
Has abstractyes

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