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Record W4387817630 · doi:10.1002/cjce.25120

Mass transfer in emulsion polymerization: An experimental and modelling study

2023· article· en· W4387817630 on OpenAlexvenueno aff
Estela Kamile Gelinski, Nida Sheibat‐Othman, Timothy F. L. McKenna

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicMembrane Separation and Gas Transport
Canadian institutionsnot available
FundersAgence Nationale de la Recherche
KeywordsPolymerizationEmulsion polymerizationChain transferPrecipitation polymerizationBulk polymerizationChain-growth polymerizationMonomerPolymer chemistryInterphaseMolar mass distributionMaterials scienceChemical engineeringRadical polymerizationChemistryPolymerComposite material

Abstract

fetched live from OpenAlex

Abstract A model is proposed to describe the impact of interphase monomer transfer on the emulsion polymerization of vinylidene fluoride (VDF). The model is validated with experimental data of the rate of polymerization and particle size distribution (PSD). During a typical emulsion polymerization process, the VDF monomer is in a gas or supercritical state, and thus much lighter than the aqueous phase in which the polymerization takes place. For this reason, the flux of monomer into the aqueous phase can depend on the type, number, and distribution of agitators on the shaft, as well as the rotation rate. The new model incorporates the interphase mass transfer coefficient into a standard emulsion polymerization model to demonstrate the impact of the agitation (in the broadest sense) on the rate of polymerization and the PSD.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.294

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 head0.016
GPT teacher head0.215
Teacher spread0.199 · 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 designSimulation or modeling
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

Citations11
Published2023
Admission routes1
Has abstractyes

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