MétaCan
Menu
Back to cohort
Record W2069406731 · doi:10.1063/1.4916584

The tunneling magnetoresistance current dependence on cross sectional area, angle and temperature

2015· article· en· W2069406731 on OpenAlexafffund
Z. H. Zhang, Lihui Bai, C.‐M. Hu, Simon Hemour, Kehui Wu, Xiaolong Fan, Ding‐Jiang Xue, D. Houssameddine

Bibliographic record

VenueAIP Advances · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsPolytechnique MontréalUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship CouncilCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsMagnetoresistanceCondensed matter physicsQuantum tunnellingTunnel magnetoresistanceFerromagnetismCurrent (fluid)Materials scienceSpin polarizationPolarization (electrochemistry)ElectronMagnetic fieldPhysicsChemistry

Abstract

fetched live from OpenAlex

The magnetoresistance of a MgO-based magnetic tunnel junction (MTJ) was studied experimentally. The magnetoresistance as a function of current was measured systematically on MTJs for various MgO cross sectional areas and at various temperatures from 7.5 to 290.1 K. The resistance current dependence of the MTJ was also measured for different angles between the two ferromagnetic layers. By considering particle and angular momentum conservation of transport electrons, the current dependence of magnetoresistance can be explained by the changing of spin polarization in the free magnetic layer of the MTJ. The changing of spin polarization is related to the magnetoresistance, its angular dependence and the threshold current where TMR ratio equals zero. A phenomenological model is used which avoid the complicated barrier details and also describes the data.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.020
GPT teacher head0.274
Teacher spread0.254 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueAIP AdvancesSame topicMagnetic properties of thin filmsFrench-language works237,207