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Record W2117357673 · doi:10.1177/8756087911407921

Effect of initial crystalline morphology on properties of polypropylene cast films

2011· article· en· W2117357673 on OpenAlexafffund
Seyed H. Tabatabaei, Abdellah Ajji

Bibliographic record

VenueJournal of Plastic Film & Sheeting · 2011
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsPolytechnique Montréal
FundersGovernment of Canada
KeywordsMaterials scienceCrystallinityLamellar structureOxygen permeabilityUltimate tensile strengthComposite materialDifferential scanning calorimetryPolypropyleneMorphology (biology)ToughnessExtrusionAmorphous solidMicrostructureCrystallographyOxygen

Abstract

fetched live from OpenAlex

Three polypropylene cast films of different initial morphologies (only spherulitic structure, coexisting rows of lamellae and spherulites, and lamellar structure) were prepared by extrusion followed by stretching using a chill roll. The effects of the original morphology on the orientation, mechanical responses, tear resistance, and oxygen permeability were investigated. The crystallinity and crystal size distribution of the films were studied using differential scanning calorimetry (DSC). The orientation of crystalline and amorphous phases were measured using wide angle X-ray diffraction and Fourier transform—infrared. The precursor film with the lamellar morphology showed much larger crystallinity, crystalline alignment, Young’s modulus, tensile strength, and tensile toughness along the machine direction, but smaller barrier to oxygen compared to the precursors with the only spherulitic structure and coexisting rows of lamellae and spherulites. The obtained results were discussed in terms of the miocrostructure of the precursor films.

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 score0.002
Threshold uncertainty score0.005

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.261
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 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

Citations18
Published2011
Admission routes2
Has abstractyes

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