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Record W2135686254 · doi:10.1139/p00-017

Magnetic nanostructures. From physical principles to spintronics

2000· article· en· W2135686254 on OpenAlexvenueno aff
B. Heinrich

Bibliographic record

VenueCanadian Journal of Physics · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsnot available
Fundersnot available
KeywordsSpintronicsNanotechnologyPhysicsEngineering physicsElectronic materialsNanostructureCondensed matter physicsFerromagnetismMaterials science

Abstract

fetched live from OpenAlex

A brief summary of underlying principles governing ultrathin film magnetic nanostructures and magnetoelectronics will be presented. The presentation will be based more on physical intuition than on rather complex physical and mathematical models in order to bring this new and rapidly expanding field to a broad audience. The success of this field has been based on the ability to create new structures in which interfaces play a crucial role. Three major phenomena have strongly affected progress in the development of new magnetic materials based on ultrathin films: (a) interface anisotropies; (b) interlayer exchange coupling; and (c) magneto-electron transport. The great progress in the study of ultrathin film multilayers and films patterned with submicrometre lateral geometries has led to a new class of electronic devices whose operation is based upon the spin-polarized character of the electronic carriers. "Magnetoelectronics and spintronics" are terms used to mark the development of very small spin-polarized electronic devices . Some latest developments in magnetic sensors and magnetic RAM will be presented to emphasize the importance of spintronics in the emerging technologies of the 21st century.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.945
Threshold uncertainty score0.998

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.198
Teacher spread0.189 · 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.

Study designOther design
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

Citations39
Published2000
Admission routes1
Has abstractyes

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