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Record W2896886024 · doi:10.1063/1.2749469

Magnetic anisotropies in ultrathin iron films grown on the surface-reconstructed GaAs substrate

2007· article· en· W2896886024 on OpenAlexafffund
B. Aktaş, B. Heinrich, Georg Woltersdorf, R. Urban, Л. Р. Тагиров, F. Yıldız, K. Özdoğan, Mustafa Özdemir, Ö. Yalçın, Bulat Rameev

Bibliographic record

VenueJournal of Applied Physics · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAnisotropyMagnetic anisotropyCondensed matter physicsMaterials scienceFerromagnetic resonanceSubstrate (aquarium)EpitaxyFerromagnetismMagnetic fieldMagnetizationOpticsLayer (electronics)Composite materialPhysics

Abstract

fetched live from OpenAlex

Magnetic anisotropies of epitaxial ultrathin iron films grown on the surface-reconstructed GaAs substrate were studied. Ferromagnetic resonance technique was exploited to determine magnetic parameters of the films in the temperature range of 4–300K. Extraordinary angular dependence of the FMR spectra was explained by the presence of fourfold and twofold in-plane anisotropies. A strong in-plane uniaxial anisotropy with magnetic hard axis along the [11¯0] crystallographic direction is present at the GaAs∕Fe(001) interface while a weak in-plane uniaxial anisotropy for the Fe grown on Au has its easy axis oriented along [11¯0]. A linear dependence of the magnetic anisotropies as a function of temperature suggests that the strength of the in-plane uniaxial anisotropy is affected by the magnetoelastic anisotropies and differential thermal expansion of contacting materials.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.011
GPT teacher head0.208
Teacher spread0.197 · 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 designBench or experimental
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

Citations38
Published2007
Admission routes2
Has abstractyes

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