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Record W2516525654 · doi:10.1002/cjce.22640

Modelling particle growth under saturated and starved conditions in emulsion polymerization

2016· article· en· W2516525654 on OpenAlexvenueno aff
Barthélémy Brunier, Nida Sheibat‐Othman, Sami Othman, Yves Chevalier, Élodie Bourgeat‐Lami

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsnot available
FundersAgence Nationale de la Recherche
KeywordsEmulsion polymerizationParticle (ecology)PolymerNucleationParticle sizeParticle-size distributionPolymerizationMonomerDiffusionSaturation (graph theory)Materials scienceRadical polymerizationEmulsionPolymer chemistryChemistryThermodynamicsChemical engineeringChemical physicsPhysical chemistryOrganic chemistryComposite materialPhysicsMathematics

Abstract

fetched live from OpenAlex

Abstract Modelling of particle growth under saturated and starved conditions in emulsion polymerization was investigated in order to allow describing the broadening of the particle size distribution and account for the effects of restricted diffusion inside the monomer‐swollen polymer particles. In emulsion polymerization, if particle nucleation and coagulation are avoided, the reaction proceeds as a consequence of radical capture, desorption, and termination reactions inside the particles. Therefore, first, investigation of radical entry and desorption models was done under saturation of polymer particles with monomer, where diffusion parameters are constant. The discrimination criterion of the different models was based on fitting the reaction and the total particle size distribution. Indeed, the broadening of the particle size distribution was found to reveal a dependency of radical capture on the particle size; such an effect would be misestimated if only the mean particle size is considered. Second, the models for starved conditions that account for the variation of radical diffusion inside the polymer particles, such as the gel and glass effects, were investigated with comparison to a wide variety of experimental conditions spanning from weak to strong gelation. The dominating mechanisms as well as the interests of both intervals are highlighted.

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 score0.033
Threshold uncertainty score0.181

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 science0.0000.000
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 head0.009
GPT teacher head0.186
Teacher spread0.177 · 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

Citations10
Published2016
Admission routes1
Has abstractyes

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