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Record W3205296976 · doi:10.1177/00037028211049242

Raman Investigation of the Processing Structure Relations in Individual Poly(ethylene terephthalate) Electrospun Fibers

2021· article· en· W3205296976 on OpenAlexafffund
Arnaud W. Laramée, Catherine Lanthier, Christian Pellerin

Bibliographic record

VenueApplied Spectroscopy · 2021
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCrystallinityRaman spectroscopyMaterials sciencePolymerFiberEthyleneSynthetic fiberPoly ethyleneComposite materialConfocalChemical engineeringChemistryOpticsOrganic chemistry

Abstract

fetched live from OpenAlex

*These authors contributed equally.Electrospun fibers often exhibit enhanced properties at reduced diameters, a characteristic now widely attributed to a high molecular orientation of the polymer chains along the fiber axis. A parameter that can affect the molecular organization is the type of collector onto which fibers are electrospun. In this work, we use polarized confocal Raman spectromicroscopy to determine the incidence of the three most common types of collectors on the molecular orientation and structure in individual fibers of a broad range of diameters. Poly(ethylene terephthalate) is used as a model system for fibers of weakly crystalline polymers. A clear correlation emerges between the choice of collector, the induced molecular orientation, the fraction of trans conformers, and the degree of crystallinity within fibers. Quantitative structural information gathered by Raman contributes to a general description of the mechanism of action of the collectors based on the additional strain they exert on the forming fibers.

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 score0.072
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.008
GPT teacher head0.242
Teacher spread0.234 · 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

Citations5
Published2021
Admission routes2
Has abstractyes

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