MétaCan
Menu
Back to cohort
Record W1996940601 · doi:10.1021/ma100622b

Catalytic Chain Transfer Mediated Emulsion Polymerization: Compartmentalization and Its Effects on the Molecular Weight Distribution

2010· article· en· W1996940601 on OpenAlexaff
Mary E. Thomson, Niels M. B. Smeets, Johan P. A. Heuts, Jan Meuldijk, Michael F. Cunningham

Bibliographic record

VenueMacromolecules · 2010
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsQueen's University
Fundersnot available
KeywordsCompartmentalization (fire protection)Chain transferChemistryPolymerEmulsion polymerizationPolymerizationEmulsionPolymer chemistryViscosityMacromoleculePopulationChemical engineeringMolar mass distributionCatalysisRadical polymerizationMaterials scienceOrganic chemistryBiochemistryComposite material

Abstract

fetched live from OpenAlex

We present the first population balance calculations which encompass the complete molecular weight distribution (MWD) to discuss the implications of both radical and catalytic chain transfer agent (CCTA) compartmentalization in a catalytic chain transfer (CCT) mediated emulsion polymerization system. Compartmentalization effects are attributed to reduced frequencies of entry and exit of the CCTA (bis[(difluoroboryl)dimethylglyoximato]cobalt(II) or COBF). Two limiting scenarios were identified. In instances of fast CCTA entry and exit, monomodal MWDs are obtained governed by a global CCTA concentration. In instances of slow entry and exit, bimodal MWDs are obtained; one peak can be attributed to the generation of a bimolecular termination product produced in polymer particles devoid of CCTA, while a transfer-derived peak can be attributed to polymer particles containing one or more CCTA molecules. We present theoretical evidence that experimentally observed multimodal MWDs ( Macromolecules 2009, 42, 7332−7341) originate from a reduced mobility of the CCTA and that when viscosity is high in the polymer particles, compartmentalization of the CCTA becomes important.

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 score0.013
Threshold uncertainty score0.668

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 head0.005
GPT teacher head0.203
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

Citations15
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueMacromoleculesSame topicAdvanced Polymer Synthesis and CharacterizationFrench-language works237,207