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Record W4406847456 · doi:10.47745/auseme-2024-0005

Comparative Study of Dielectric Properties and Other Physical Properties of Superparamagnetic Iron Oxide Nanoparticles and Polyethylene Nanocomposites

2025· article· en· W4406847456 on OpenAlexfundno aff
Taraneh Javanbakht, Sophie Laurent, Dimitri Stanicki, Éric David

Bibliographic record

VenueActa Universitatis Sapientiae Electrical and Mechanical Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicDielectric materials and actuators
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNanocompositeSuperparamagnetismMaterials scienceDielectricNanoparticlePolyethylene oxidePolyethyleneChemical engineeringComposite materialNanotechnologyPolymerMagnetizationOptoelectronics

Abstract

fetched live from OpenAlex

The present paper proposes a new investigation of the dielectric properties of superparamagnetic iron oxide nanoparticles (SPIONs)/PE nanocomposites in comparison with the neat polymer at different temperatures. The SPIONs used were without or with positively or negatively surface charge. Different frequency-domain dielectric responses were observed for the different samples. The usual decrease of the values of the real part of the permittivity of all the three SPIONs nanocomposites in the range was observed with the increase of temperature. Moreover, the values of the real part of the permittivity of PE-bare SPIONs increased slightly at lower frequencies, whereas those of PE-positively charged SPIONs and PE-negatively charged SPIONs were constant at higher frequencies and showed an increase at medium frequencies and a plateau at lower frequencies. The imaginary part of their permittivity also showed dielectric responses for the samples.

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 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 score0.088
Threshold uncertainty score0.650

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)0.0000.000

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 head0.183
Teacher spread0.175 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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