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Record W4206549497 · doi:10.3390/nano12020184

Muon Irradiation of ZnO Rods: Superparamagnetic Nature Induced by Defects

2022· article· en· W4206549497 on OpenAlexafffund
Cody Landry, Alexander H. Morrison, Mehdi Esmaeili, Khashayar Ghandi

Bibliographic record

VenueNanomaterials · 2022
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSuperparamagnetismMaterials scienceRodCoprecipitationPhotoluminescenceIrradiationCondensed matter physicsDiffractionMagnetic fieldNuclear magnetic resonanceAnalytical Chemistry (journal)MagnetizationOpticsChemistryOptoelectronicsInorganic chemistryNuclear physicsPhysics

Abstract

fetched live from OpenAlex

In this work, through a combination of photoluminescence spectroscopy, X-ray powder diffraction and magnetic measurements, it is determined that ZnO rods, made hydrothermally using a combination of magnetic field with respect to the force of gravity, exhibit superparamagnetic properties which emerge from Zn defects. These Zn defects result in a size-dependent superparamagnetic property of the rods. Red emissions, characteristic of Zn vacancies, and magnetic susceptibility both increased with decreasing rod size. The ZnO rods have significantly larger superparamagnetic cluster sizes (one order of magnitude) and lower fluctuation rates when compared to other superparamagnetic particles.

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 categoriesInsufficient payload (model declined to judge)
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 score0.007
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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 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
Published2022
Admission routes2
Has abstractyes

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