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Record W3115864220 · doi:10.1002/mren.202000052

Kinetics of MMA Atom Transfer Radical Polymerization Initiated by Reducing Agent in Stirred Batch Emulsion Reactor

2020· article· en· W3115864220 on OpenAlexaff
Mohammed Awad, Ramdhane Dhib, Thomas A. Duever

Bibliographic record

VenueMacromolecular Reaction Engineering · 2020
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsEmulsion polymerizationPolymerizationDispersityPolymer chemistryGel permeation chromatographyAtom-transfer radical-polymerizationRadical polymerizationChain transferMethyl methacrylateMolar mass distributionPolymerMaterials scienceChemical engineeringMonomerChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Ab initio emulsion atom transfer radical polymerization (ATRP) differs from regular emulsion polymerization because the kinetic and thermodynamic aspects of each process are very unlikely alike. This paper presents a kinetic analysis of activator generated by electron transfer (AGET) ATRP of methyl methacrylate (MMA) in a stirred emulsion reactor. The focus of the study is to assess the variation of the monomer content in the organic phase and the rate polymerization for different reaction temperatures, as well as the impact of surfactant content and stirring speed on latex stability. Poly(methyl methacrylate) (PMMA) polymer samples are analyzed by means of gravimetry, dynamic light scattering, gel permeation chromatography, and HNMR techniques to determine monomer conversion, polymer particle diameter, molecular weight distribution, and polymer molecular structure, respectively. The results show the production of PMMA of narrow polydispersity index ( Ð ) and low molar mass ( M n ) for MMA conversion around 60% and detect two‐regions instead of a three‐regions trend of rate of polymerization ( R p ) as conventional emulsion polymerization. The reaction rate increases during the nucleation stage and then flattens over an invariant trend which confirms a living feature of the AGET ATRP polymerization. The average number of radicals per latex particle ( ñ ) is also debated.

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 score0.161
Threshold uncertainty score0.976

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 head0.012
GPT teacher head0.211
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 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

Citations5
Published2020
Admission routes1
Has abstractyes

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