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Record W2975634950 · doi:10.1122/1.5102177

Effect of clay particles size and location on coalescence in PMMA/PS blends

2019· article· en· W2975634950 on OpenAlexaff
Julie Genoyer, Nicole R. Demarquette, J. Soulestin

Bibliographic record

VenueJournal of Rheology · 2019
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsMaterials scienceMontmorilloniteCoalescence (physics)HalloysiteInterphaseNanoparticleComposite materialChemical engineeringNanotechnology

Abstract

fetched live from OpenAlex

The addition of six different clays (laponite, montmorillonite, halloysite, and their organomodified counterparts) to poly(methyl methacrylate), polystyrene, and their blends was studied. The morphologies of the obtained composites were studied using transmission electron microscopy and scanning electron microscopy. Small angle oscillatory shear experiments, as well as shear induced coalescence tests, were carried out to evaluate the role of the clay as a coalescence inhibitor. Using the six different clays enabled the evaluation of the effect of the clay location and the clay platelet size for a given location (matrix, dispersed phase, interphase) on the coalescence phenomenon. A decrease of the dispersed phase of the blend was generally observed upon the addition of the clay. Clays located exclusively in the matrix (laponite, montmorillonite, halloysite, and modified halloysite) were shown to migrate to the interface during coalescence tests, inducing a decrease of coalescence at a certain extent of migration. Modified montmorillonite, located at the interface, was the most efficient clay at inhibiting coalescence, due to relaxation of Marangoni stresses with an important barrier effect. Overall, it was shown that having a certain size of a nanoparticle is essential for it to locate at the interface and inhibit coalescence. Nanoparticles with a larger size than the droplets are not able to locate at the interface and, therefore, do not have an effect on coalescence. Conversely, nanoparticles whose size is 10% or less of the droplet were found to be well dispersed in the whole blend. These particles did not have a preferred location nor had an effect on coalescence.

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 score0.038
Threshold uncertainty score0.153

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.236
Teacher spread0.231 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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