MétaCan
Menu
Back to cohort
Record W1970873390 · doi:10.1021/ma102121t

Miscible and Core−Sheath PS/PVME Fibers by Electrospinning

2011· article· en· W1970873390 on OpenAlexafffund
Dominic Valiquette, Christian Pellerin

Bibliographic record

VenueMacromolecules · 2011
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrospinningMaterials sciencePolystyreneMiscibilityChemical engineeringPhase (matter)Phase diagramSolventPolymer chemistryEvaporationLower critical solution temperaturePolymer blendPolymerCastingTernary operationComposite materialCopolymerChemistryOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

We demonstrate that miscible and phase-separated fibers of the blend between polystyrene (PS) and poly(vinyl methyl ether) (PVME) can be electrospun by appropriate selection of the solvent. Solutions in benzene allow preparing miscible fibers with composition ranging from pure PS to PS/PVME 70/30. Results indicate that the rapid solvent evaporation during electrospinning has no significant influence on the phase behavior of polymer blends when the system is miscible throughout the ternary phase diagram. On the other hand, fibers electrospun from chloroform solutions show a clear phase separation because of a closed immiscibility loop. They are nevertheless highly malleable, in contrast with the brittle films obtained by solution casting. The confinement and solvent evaporation kinetic lead to a core−sheath structure, with the interior composed of the PS-rich phase and the surface highly enriched in PVME, as opposed to microdomains in cast films. The shell can be extracted rapidly and efficiently by a 10 s treatment in water, converting the mat from fully wettable to highly hydrophobic.

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 score0.064
Threshold uncertainty score0.694

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)0.0010.000

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 head0.017
GPT teacher head0.237
Teacher spread0.221 · 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

Citations28
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueMacromoleculesSame topicElectrospun Nanofibers in Biomedical ApplicationsFrench-language works237,207