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Record W2489446915 · doi:10.1021/acs.iecr.5b02141

Rheology of PP/PP-<i>g</i>-MA and PP/PP-<i>g</i>-AA Blends and Incidence on Orientation and Crystalline Structure of Their Cast Films

2015· article· en· W2489446915 on OpenAlexafffund
Amir Saffar, Seyed H. Tabatabaei, Pierre J. Carreau, Abdellah Ajji, Musa R. Kamal

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsMcGill UniversityPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLamellar structurePolypropyleneMaterials scienceMaleic anhydrideMicroporous materialMembranePolymer chemistryChemical engineeringRheologyCopolymerRelaxation (psychology)Polymer blendPolymerComposite materialChemistry

Abstract

fetched live from OpenAlex

The intrinsic hydrophobic character of polypropylene limits its performance in many porous membrane applications. This can be improved by hydrophilic modification of the film surface through blending with hydrophilic polymers. For producing the precursor films and, consequently, microporous membranes with the appropriate crystalline lamellar morphology, the polypropylene chains should preserve their elongated form to serve as initial nuclei for the later development of lamellar crystals. The relaxation time of the chains is the most important factor for this stage. Commercial maleic anhydride and acrylic acid grafted polypropylenes were melt blended with a polypropylene at different weight ratios. The results showed that the modifiers lowered the crystalline orientation of the blends as compared to neat polypropylene films. The effect of the modifier on the melt relaxation spectra of the blends was investigated, and a linear relationship was found between the characteristic relaxation time of the blends and their crystalline orientation function.

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)0.001
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 score0.003
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.076
GPT teacher head0.307
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.

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

Citations7
Published2015
Admission routes2
Has abstractyes

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