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Record W3087991779 · doi:10.1002/app.49959

Polyvinylidene fluoride nanofibers obtained by electrospinning and blowspinning: Electrospinning enhances the piezoelectric <scp>β‐phase</scp> – myth or reality?

2020· article· en· W3087991779 on OpenAlexafffund
Cherif M. Azzaz, L. H. C. Mattoso, Nicole R. Demarquette, Ricardo J. Zednik

Bibliographic record

VenueJournal of Applied Polymer Science · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsElectrospinningPolyvinylidene fluorideNanofiberPiezoelectricityMaterials scienceElectric fieldComposite materialPhase (matter)PolymerChemistry

Abstract

fetched live from OpenAlex

Abstract Considerable effort has been devoted to improving the properties of PVDF (polyvinylidene fluoride), arguably the most technologically important piezoelectric polymer. Electrospinning has been found to be a particularly effective method of producing PVDF nanofibers with superior piezoelectric properties due to the resulting exceptionally high fraction of the piezoelectrically active crystalline β‐phase. It is typically assumed that the high external electric fields applied during electrospinning enhance the formation of this β‐phase, with the confused literature offering various unsatisfactory mechanistic explanations. However, by comparing PVDF nanofibers produced by two different processes (electrospinning and blowspinning), we show that the electric field is entirely unnecessary; indeed, the crystallization dynamics are principally driven by the applied mechanical stress, as evidenced by structurally identical 200 nm diameter PVDF fibers produced with and without external electric fields.

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 categoriesMeta-epidemiology (narrow)
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 score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.012
GPT teacher head0.243
Teacher spread0.231 · 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

Citations18
Published2020
Admission routes2
Has abstractyes

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