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Record W2259460805 · doi:10.1063/1.4936626

Magnetometry of micro-magnets with electrostatically defined Hall bars

2015· article· en· W2259460805 on OpenAlexafffund
Dany Lachance-Quirion, Julien Camirand Lemyre, Laurent Bergeron, Christian Sarra‐Bournet, Michel Pioro-Ladrière

Bibliographic record

VenueApplied Physics Letters · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsCanadian Institute for Advanced ResearchUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsCondensed matter physicsHall effectMagnetMagnetometerMagnetic fieldMagnetizationFerromagnetismHall effect sensorBar (unit)Demagnetizing fieldMaterials scienceMagnetoresistancePhysics

Abstract

fetched live from OpenAlex

Micro-magnets are key components for quantum information processing with individual spins, enabling arbitrary rotations and addressability. In this work, characterization of sub-micrometer sized CoFe ferromagnets is performed with Hall bars electrostatically defined in a two-dimensional electron gas. Due to the ballistic nature of electron transport in the cross junction of the Hall bar, anomalies such as the quenched Hall effect appear near zero external magnetic field, thus hindering the sensitivity of the magnetometer to small magnetic fields. However, it is shown that the sensitivity of the diffusive limit can be almost completely restored at low temperatures using a large current density in the Hall bar of about 10 A/m. Overcoming the size limitation of conventional etched Hall bars with electrostatic gating enables the measurement of magnetization curves of 440 nm wide micro-magnets with a signal-to-noise ratio above 103. Furthermore, the inhomogeneity of the stray magnetic field created by the micro-magnets is directly measured using the gate-voltage-dependent width of the sensitive area of the Hall bar.

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)0.000
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 score0.000
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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)0.0000.000

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 head0.008
GPT teacher head0.197
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 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

Citations7
Published2015
Admission routes2
Has abstractyes

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