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Obtention and Characterization of Polypropylene, Calcium Carbonate and Poly(ethylene-co-vinyl acetate) Composites

2012· article· en· W2159994671 on OpenAlexvenueno aff
J Alberton, Sílvia Maria Martelli, Valdir Soldi

Bibliographic record

VenueJournal of Research Updates in Polymer Science · 2012
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials sciencePolypropyleneComposite materialExtrusionCrystallinityUltimate tensile strengthEthylene-vinyl acetateReactive extrusionThermal stabilityFlexural strengthCalcium carbonatePolymerComposite numberHeat deflection temperatureIzod impact strength testChemical engineeringCopolymer

Abstract

fetched live from OpenAlex

In the increasingly competitive market, the survival of the industries that manufacture components or pieces of polymer is strictly linked to the reduction of production costs. An alternative could be the use of composites of polypropylene, calcium carbonate and poly(ethylene-co-vinyl acetate) for the production of thermoplastics sheets. The thermoplastics sheets obtained by extrusion and co-extrusion processes were characterized through the chemical, physical, thermal, mechanical and morphological characteristics of materials, enabling the performance analysis of the production processes and application to the design of components or parts. The results showed that the addition of 30 wt% CaCO3-EVA increased the thermal stability of polypropylene (PP) around 32°C, decreasing the processing temperature of composites in 15°C, also by decreasing the crystallinity of the polymer from 43% to 30% and the deflection temperature of plastics under flexural load in the edgewise position (DTUL) from 122°C to 107°C. Regarding to the mechanical tests, the yield stress of the composites obtained by extrusion and co-extrusion processes decreased with the addition of CaCO3-EVA. According with the obtained results, we suggest that PP/CaCO3-EVA composites could be used in the production of polymeric parts or components where tensile strengths higher than 25 MPa are not required and for service temperatures between 30°C and 70°C.

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)0.004
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 score0.022
Threshold uncertainty score0.643

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.002
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 head0.048
GPT teacher head0.356
Teacher spread0.308 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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