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Record W2008211226 · doi:10.3139/217.2017

Polypropylene-Clay Nanocomposites Fibers Structure and Performance

2007· article· en· W2008211226 on OpenAlexaff
Abdellah Ajji, J. Denault, Danielle L. Cote, Martin Bureau, David Trudel‐Boucher

Bibliographic record

VenueInternational Polymer Processing · 2007
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceComposite materialPolypropyleneUltimate tensile strengthNanocompositeModulusComposite numberFiberScanning electron microscopeDiffractionTransverse planeFlexural strengthOptics

Abstract

fetched live from OpenAlex

Abstract Fibers from Polypropylene (PP) and polypropylene nanocomposite (PNC) were produced using a fiber spinning process. Various amounts of different clays were added to the PP matrix. The structure of PP and PNC fibers was evaluated using field emission scanning electron microscopy (FE-SEM) and X-ray diffraction. The crystalline axes orientation factors were determined from wide-angle X-ray diffraction pole figures of (110) and (040) reflections for PP and of (001) for clay. The d-spacing of the (001) clay crystalline plane, indicative of the clay dispersion, was determined from the intensity −2 θ plots superimposed on the two dimensional X-ray diagrams. The results obtained for the d-spacing at small angles indicated that the clay in the PNC maintained its intercalated distance at low loadings whereas at higher loadings, some aggregation was observed. Results on orientation of the clay (001) axis (normal to the clay platelets plane) indicated that it was oriented perpendicular to the machine direction, which is expected. Its orientation in the normal and transverse directions was different, suggesting that clay platelets were not randomly distributed in the transverse plane, which was confirmed from SEM observations. The orientation of PP c-axis in the fibers was slightly higher for the nano-composite that the pure resin. Tensile modulus, strength and elongation at break for both PP and PNC fibers increased with increasing draw ratio. Flexural modulus and strength of laminates made by consolidation of the PNC fibers were higher than those of consolidated pure PP fibers as well as those of bulk PP or PNC.

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 score0.077
Threshold uncertainty score0.596

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 communication0.0000.001
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 head0.008
GPT teacher head0.238
Teacher spread0.230 · 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

Citations3
Published2007
Admission routes1
Has abstractyes

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