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Record W2778936465 · doi:10.3390/polym10010033

Polypropylene-Based Porous Membranes: Influence of Polymer Composition, Extrusion Draw Ratio and Uniaxial Strain

2017· article· en· W2778936465 on OpenAlex
Pilar Castejón, Kian Habibi, Amir Saffar, Abdellah Ajji, Antonio B. Martínez, D. Arencón

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePolymers · 2017
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceDifferential scanning calorimetryThermogravimetric analysisExtrusionPolypropyleneComposite materialScanning electron microscopePorosityThermal stabilityPolymerMicroporous materialChemical engineering

Abstract

fetched live from OpenAlex

Several commercial grades of homo-polymer and its blends were selected to prepare microporous membranes through melt extrusion-annealing-uniaxial stretching technique (MEAUS). Branched or very fluid polypropylene was employed to modify the polymeric composition. In some blends, micro-sized calcium carbonate was added. We analysed the influence of sample composition, extrusion draw ratio, and we performed a deep study concerning the uniaxial strain rate, using in some cases extreme strain rates and strain extents. The crystalline features were studied by Differential Scanning Calorimetry (DSC), and the morphology of porous structure was analyzed through Scanning Electron Microscopy (SEM). Thermal stability and thermomechanical performance was measured by thermogravimetric analysis (TGA) and dynamic-mechanical-thermal (DTMA) study. A close relationship was found between crystalline characteristics, porous morphology and the trends registered for permeability.

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.

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 score0.006
Threshold uncertainty score0.813

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 studies0.0010.001
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 head0.015
GPT teacher head0.245
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