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Record W2048379362 · doi:10.1002/app.32947

Influence of supercritical CO<sub>2</sub> on the interactions between maleated polypropylene and alkyl‐ammonium organoclay

2010· article· en· W2048379362 on OpenAlexaff
J. Liu, Michael R. Thompson, Michael P. Balogh, Richard L. Speer, Paula D. Fasulo, William R. Rodgers

Bibliographic record

VenueJournal of Applied Polymer Science · 2010
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsMcMaster University
Fundersnot available
KeywordsOrganoclayMaterials scienceDifferential scanning calorimetrySupercritical fluidPolypropyleneExfoliation jointChemical engineeringPolymerFourier transform infrared spectroscopyPolymer chemistryAlkylAmmonium bromideComposite materialOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

Abstract Supercritical carbon dioxide (scCO 2 ) has been proposed as an effective exfoliating agent for the preparation of polymer‐layered silicate nanocomposites, though there is limited fundamental understanding of this mechanism. This study looks at the interactions of this unique green solvent with three maleated polypropylenes of varying anhydride content and molecular size with an alkyl‐ammonium organoclay. Mixtures of compatibilizers and organoclay were melt‐annealed in a high pressure batch vessel at 200°C and subjected to either a blanket of nitrogen or scCO 2 at a pressure of 9.7 MPa. The structures and properties of these melt‐annealed mixtures were characterized by X‐ray diffraction, transmission electron microscopy, Fourier Transform infrared spectroscopy, nuclear magnetic resonance spectroscopy, differential scanning calorimetry, and contact angle measurement. The results indicate that the plasticizing influence of scCO 2 aided intercalation and exfoliation for intercalants of moderate molecular size and anhydride content which would otherwise have limited diffusion into the clay galleries. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2011

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)0.001
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 score0.013
Threshold uncertainty score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.244
Teacher spread0.237 · 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

Citations7
Published2010
Admission routes1
Has abstractyes

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