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Record W2051219033 · doi:10.1063/1.4773180

Yoke-shaped MgO-barrier magnetic tunnel junction sensors

2012· article· en· W2051219033 on OpenAlexfundno aff
Junyang Chen, Nicola Carroll, J. F. Feng, J. M. D. Coey

Bibliographic record

VenueApplied Physics Letters · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsnot available
FundersUniversity of WaterlooScience Foundation IrelandEuropean Commission
KeywordsYoke (aeronautics)Quantum tunnellingMagnetoresistanceTunnel magnetoresistanceMaterials scienceFerromagnetismPerpendicularAnnealing (glass)Magnetic fieldElectrodeElectromagnetic shieldingCondensed matter physicsOptoelectronicsTunnel effectMagnetometerAnisotropyNuclear magnetic resonanceElectrical engineeringPhysicsOpticsComposite material

Abstract

fetched live from OpenAlex

Yoke-shaped sensors based on MgO-barrier magnetic tunnel junctions have been designed, fabricated, and studied; they show a good linear tunneling magnetoresistance (TMR) response. A nearly-perpendicular configuration of two ferromagnetic electrodes was set by two-step annealing together with shape anisotropy. The low-frequency noise characterization shows these yoke-shaped TMR sensors have relatively low magnetic 1/f noise. The field sensitivity is up to 27%/mT, while the field detectivity reaches 4.6 nT/Hz at 10 Hz and 460 pT/Hz at 1 kHz. These TMR sensors may be useful for applications such as biomagnetic detection.

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 categoriesMeta-epidemiology (narrow), Insufficient 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.001

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 head0.011
GPT teacher head0.197
Teacher spread0.186 · 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

Citations30
Published2012
Admission routes1
Has abstractyes

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