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Record W1978316697 · doi:10.1002/mren.201100017

A Study of Particle Nucleation in Dispersion Copolymerization of Methyl Methacrylate

2011· article· en· W1978316697 on OpenAlexafffund
Robert A. Cockburn, Timothy F. L. McKenna, Robin A. Hutchinson

Bibliographic record

VenueMacromolecular Reaction Engineering · 2011
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComonomerMethyl methacrylateDispersion polymerizationDispersion (optics)MonomerPolymer chemistryCopolymerPolymerizationNucleationParticle (ecology)Materials scienceChemical engineeringChain transferChemistryRadical polymerizationOrganic chemistryPolymerComposite materialPhysics

Abstract

fetched live from OpenAlex

Abstract The dispersion polymerization of methyl methacrylate (MMA) and its copolymerization with the bio‐renewable monomer γ‐methyl‐α‐methylene‐γ‐butyrolactone (MeMBL) is studied in a methanol/water mixture. The addition of MeMBL to an MMA dispersion decreases both rate and particle size (PS), while rate decreases and PS increases when the fraction of methanol in the continuous phase is increased. The differing effects of comonomer and continuous phase composition can be attributed to monomer partitioning and critical chain length (jcrit) of the radicals formed in solution. A cobalt(II) catalytic chain transfer agent (CCTA) was used to determine a value of 20–30 monomer units for jcrit in MMA dispersion polymerization. A distinct population of small particles, about one‐tenth as large as the 1–2 µm mature particles, was observed throughout the entire course of the dispersion polymerization; it is these particles, most likely aggregates of nuclei continuously generated in solution, that are swept up by the mature particles during growth. magnified image

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.218
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), 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

Citations14
Published2011
Admission routes2
Has abstractyes

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