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Record W1975927254 · doi:10.1103/physrevb.62.5786

Relation of domain properties to structural changes in perpendicularly magnetized ultrathin films

2000· article· en· W1975927254 on OpenAlexafffund
M. J. Dunlavy, D. Venus

Bibliographic record

VenuePhysical review. B, Condensed matter · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceAnnealing (glass)Condensed matter physicsAuger electron spectroscopyAnisotropyMagnetic domainMagnetic anisotropyMonolayerPerpendicularAnisotropy energyActivation energyDomain wall (magnetism)Nuclear magnetic resonanceMagnetic susceptibilityMagnetic fieldMagnetizationOpticsPhysicsChemistryNanotechnologyComposite material

Abstract

fetched live from OpenAlex

The influence of interface mixing upon the magnetic domain properties in perpendicularly magnetized ultrathin films has been studied using Fe/2 ML Ni/W(110) samples. Annealing of films with an Fe thickness of 1--1.5 ML produces interface mixing that can be quantified using Auger electron spectroscopy, and related to the changes in domain properties (such as the activation energy for domain wall pinning, the domain correlation length, and domain concentration) as measured by the low frequency ac magnetic susceptibility. Analysis of the susceptibility, as well as model calculations of the magnetic anisotropy, suggest that pinning is caused by the perturbation of the domain wall energy by monolayer steps in thickness. Initially, annealing smooths the film, thus increasing the domain correlation length and activation energy. Further annealing causes mixing at the Fe/Ni interface, which reduces the anisotropy, thus reducing the activation energy and increasing the domain concentration. Annealing above 550 K breaks up the film and there is no magnetic response in the measurable temperature range.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0250.001

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 head0.256
Teacher spread0.246 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2000
Admission routes2
Has abstractyes

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