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Record W4386226509 · doi:10.1063/5.0147920

Large-scale vibrating coil magnetometer for the magnetic characterization of bulk superconductors

2023· article· en· W4386226509 on OpenAlexafffund
A. Larry Arsenault, B. Charpentier-Pépin, A. Forcier, N. Nassiri, Jonathan Bellemare, Christian Lacroix, David Ménard, Frédéric Sirois, Fabrice Bernier, Jean-Michel Lamarre

Bibliographic record

VenueReview of Scientific Instruments · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsNational Research Council CanadaPolytechnique Montréal
FundersInstitut TransMedTechFonds de recherche du Québec – Nature et technologiesNational Research Council CanadaCanada First Research Excellence Fund
KeywordsMagnetometerSuperconductivityCondensed matter physicsMaterials scienceElectromagnetic coilMagnetic fieldMagnetizationMagnetic hysteresisHysteresisSuperconducting magnetNuclear magnetic resonancePhysics

Abstract

fetched live from OpenAlex

This work presents the design and validation of a vibrating coil magnetometer for the characterization of the field dependence of the critical current density of centimeter-sized bulk superconductors as an alternative to the destructive methods typically used. The magnetometer is also shown to be capable of measuring the magnetic moment in an applied field of up to 5 T for diverse magnetic materials, such as soft and hard ferromagnets and high-temperature superconducting pellets. The vibrating coil magnetometer was first optimized using finite element simulations and calibrated using a commercial vibrating sample magnetometer. The vibrating coil magnetometer was benchmarked with hysteresis measurements of a Nd2Fe14B disk made with a commercial hysteresisgraph, showing good agreement between the different setups. The magnetic hysteresis of a YBa2Cu3O7-x superconducting pellet was measured at 77 K, showing a penetration field of 1 T and an irreversibility field of 4 T. The field dependent critical current density of the superconductor was then inferred from the magnetic hysteresis measurements and extrapolated at low fields. Finally, the resulting critical current density was used to successfully reproduce the measured magnetization curve of the pellet at 2 T with finite element simulations.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.257
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.022
GPT teacher head0.264
Teacher spread0.242 · 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.

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

Citations2
Published2023
Admission routes2
Has abstractyes

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