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Record W2090816299 · doi:10.1021/la9027699

Rheological Behavior of Acid-Swellable Cationic Copolymer Latexes

2009· article· en· W2090816299 on OpenAlexaff
Beng Hoon Tan, Kam Chiu Tam, Damien Dupin, Steven P. Armes

Bibliographic record

VenueLangmuir · 2009
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCationic polymerizationCopolymerRheologyChemical engineeringPolymer chemistryChemistryPolymer scienceMaterials sciencePolymerOrganic chemistryComposite materialEngineering

Abstract

fetched live from OpenAlex

2-Vinylpyridine (2VP) was copolymerized with four different cross-linker densities ranging from 0.05 to 0.31 wt % divinylbenzene (DVB) via aqueous emulsion polymerization to produce a series of submicrometer-sized, lightly cross-linked P2VP latexes. Protonation of the 2VP residues leads to a latex-to-microgel transition due to interchain electrostatic repulsion, as confirmed by dynamic light scattering. The DVB content of these pH-responsive copolymer particles strongly affects their rheological behavior. The particle size and viscosity of the swollen cationic microgels exhibit a maximum at approximately 0.11 wt % DVB. Static light scattering results confirm this density as the minimum amount of DVB required to ensure that all P2VP chains are cross-linked (i.e. that there is no soluble fraction), thus allowing optimal swelling of the microgels. Viscosity studies shows that the solution viscosity of a P2VP microgel at low pH follows two models, depending on its concentration. For volume fractions below 0.30, the P2VP microgels behave as hard spheres, as predicted by the Batchelor equation. For more concentrated P2VP microgels (volume fractions above 0.30), the rheological behavior can be predicted using the Krieger-Dougherty model for strong particle-particle interactions; thus, this semiempirical approach provides a useful description of the aqueous solution behavior of microgel.

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 categoriesInsufficient payload (model declined to judge)
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 score0.017
Threshold uncertainty score0.998

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)0.0030.000

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 head0.010
GPT teacher head0.242
Teacher spread0.232 · 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.

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

Citations12
Published2009
Admission routes1
Has abstractyes

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