MétaCan
Menu
Back to cohort
Record W4402859545 · doi:10.1002/marc.202400403

Influence of Mixed Solvent in the Morphology and Hydrophobicity of Electrospun Polystyrene Porous Fibers

2024· article· en· W4402859545 on OpenAlexafffund
Guilherme Henrique França Melo, Uttandaraman Sundararaj

Bibliographic record

VenueMacromolecular Rapid Communications · 2024
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrospinningPolystyreneMaterials scienceContact angleSolventMorphology (biology)PorosityScanning electron microscopeFiberChemical engineeringMembraneNanometreNanoporeComposite materialPolymer chemistryPolymerNanotechnologyChemistry

Abstract

fetched live from OpenAlex

Abstract Electrospun polystyrene (PS) fibers are produced using a mixed solvent of chloroform and n,n‐dimethylformamide (DMF) to investigate the influence of the solvent ratio on the fiber surface morphology and contact angle of the obtained mats. Electrospinning is a simple processing technique for producing fibers with diameters in the range of nanometers to a few micrometers. When using the different solvent ratios for this process, porous PS membranes are created due to nonsolvent and thermally induced phase separation (N‐TIPS). The morphology of the fibers is analyzed through scanning electron microscopy (SEM), which showed that fibers have diameters between 200 nm and 6 µm. SEM also revealed that the pores present on the surface of the fibers vary from densely compacted and well‐formed nanopores with diameters in the range of 20–50 nm to larger pores with sizes of ≈100–200 nm. The pore size varied with different solvent ratios. The surface area is analyzed using the Brunauer–Emmett–Teller (BET) method and found that the polymeric fibers have a high surface area (≈35 m 2 g −1 ). The fibers with such morphology are highly hydrophobic, with a contact angle higher than 143°. These materials are excellent candidates for applications in textiles, filtration, and biomedical 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 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 score0.009
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.260
Teacher spread0.251 · 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

Citations10
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueMacromolecular Rapid CommunicationsSame topicElectrospun Nanofibers in Biomedical ApplicationsFrench-language works237,207