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Record W2334825512 · doi:10.1021/ie502300j

Influence of Stretching on the Performance of Polypropylene-Based Microporous Membranes

2014· article· en· W2334825512 on OpenAlexafffund
Amir Saffar, Pierre J. Carreau, Abdellah Ajji, Musa R. Kamal

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2014
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsMcGill UniversityPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMembraneMicroporous materialInterconnectivityPolypropyleneMaterials scienceChemical engineeringPermeationPermeability (electromagnetism)Annealing (glass)ExtrusionComposite materialPolymer chemistryChemistry

Abstract

fetched live from OpenAlex

We analyze the pore structure changes during the fabrication of polypropylene-based microporous membranes via the stretching method. The membranes were prepared via melt extrusion followed by annealing and stretching at room temperature and at an elevated temperature (cold and hot stretching steps, respectively). Understanding the pore formation mechanisms is important for effective control of the membrane performance. Hence, the pore structure along the membrane surface and across the thickness, which determined the size, number, and interconnectivity of the pores, was analyzed to quantify the effect of stretching on the membrane performance. The cold stretching step was found to be the important one for promoting interconnection between the pores. Furthermore, it was shown that applying a low strain rate improved the permeability of the membranes. Finally, no maximum was observed in the permeability by increasing the stretch ratio during the hot stretching step.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.051
GPT teacher head0.275
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), 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

Citations50
Published2014
Admission routes2
Has abstractyes

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