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Record W2972223763 · doi:10.1021/acsaelm.9b00430

Interface-Engineered Control of Fe/Cu Thin Film Magnetism

2019· article· en· W2972223763 on OpenAlex
R. D. Desautels, Vinod K. Paidi, J. W. Freeland, Chin Shueh, Ko‐Wei Lin, J. van Lierop

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACS Applied Electronic Materials · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Science and Technology, TaiwanCanada Foundation for Innovation
KeywordsMagnetismMaterials scienceSuperparamagnetismAlloyCoercivityThin filmCondensed matter physicsMetallurgyNanotechnologyMagnetizationMagnetic field

Abstract

fetched live from OpenAlex

We show that the magnetism of Fe/Cu nanostructured thin films can be controlled by adjusting an interfacial FeCu alloy formed during in situ ion-beam bombardment of the Fe atoms, promoting intermixing between the Fe and Cu, forming an FeCu alloy. This intermixing results in prominent changes to the inter- and intracrystallite interactions which govern the magnetism. With increased interfacial alloy content, the films were modified from a multilayer to a dispersion morphology. This control over increased disorder tuned the magnetic interactions, such as enabling the coexistence of superparamagnetism of Fe nanocrystallites and magnetic ordering of the FeCu component so that a film’s coercivity increased with warming near TC.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
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 score0.076
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0170.001

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 head0.003
GPT teacher head0.190
Teacher spread0.187 · 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