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Record W2013510497 · doi:10.3139/217.2815

Simha-Somcynsky Equation of State Modeling of the PVT Behavior of PP/Clay-Nanocomposite/CO<sub>2</sub> Mixtures

2014· article· en· W2013510497 on OpenAlexaff
Md. Mahmudul Hasan, Chul B. Park

Bibliographic record

VenueInternational Polymer Processing · 2014
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPolypropyleneMaterials scienceSwellingPolymerOrganoclayNanocompositeSupercritical fluidVolume (thermodynamics)Supercritical carbon dioxidePolymer nanocompositeComposite materialNanoparticleAbsorption (acoustics)Blowing agentChemical engineeringPolymer chemistryThermodynamicsNanotechnologyChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The Pressure-Volume-Temperature (PVT) property of polymer nanocomposite (PNC)/gas solutions is an important fundamental property in the foaming of PNC. However, accurate data have not yet been reported. We examined the PVT behaviors of polypropylene (PP) and PP/organoclay polymer nanocomposite (PP-PNC) by monitoring the swelling changes of the polymer melt in supercritical carbon dioxide (scCO 2 ). A model was adopted that describes the PVT behaviors of PP-PNC with and without dissolved gas. Based on the model, a PNC consists of two sections: a hard section (a nanoparticle surrounded by solidified polymer) and a soft section (neat polymer). It was observed that an infusion of nanoparticles decreased the swelling. It seems that the hard section had a minimal free volume in which to dissolve the blowing agents, and that the number of hard sections increased with the infusion of nanoparticles. As a result, the total gas absorption capacity of the system decreased, and consequently, the swelling also decreased.

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 score0.061
Threshold uncertainty score0.500

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 communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.259
Teacher spread0.243 · 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
Published2014
Admission routes1
Has abstractyes

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