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Record W2088232393 · doi:10.1021/ma011260j

A Rheological Evaluation of the Interactions in Water between a Cationic Cellulose Ether and Sodium Poly(2-acrylamido-2-methylpropanesulfonates)

2001· article· en· W2088232393 on OpenAlexaff
Roger C. W. Liu, Yotaro Morishima, Françoise M. Winnik

Bibliographic record

VenueMacromolecules · 2001
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPolyelectrolyteRheologyCellulosePolymer chemistryShear thinningCationic polymerizationThixotropyChemistryShear rateChemical engineeringCopolymerApparent viscosityThermodynamicsMaterials sciencePolymerOrganic chemistryComposite materialPhysics

Abstract

fetched live from OpenAlex

The rheology of solutions of a cationic cellulose ether (JR400) and either sodium poly(2-acrylamido-2-methylpropanesulfonate) (PAMPS) or a copolymer of sodium 2-acrylamido-2-methylpropanesulfonate and N - n -dodecylmethacrylamide (PAMPS-Dod) has been examined over a wide composition range in the semidilute regime (10 g L -1 ) by steady shear and time-dependent steady shear measurements. Miscible combinations of pairs of oppositely charged polyelectrolytes form in two composition domains: (1) a polyanion-poor region which exhibits shear thinning characteristics and (2) a polyanion-rich region which presents Newtonian behavior at low shear rates and, as the shear rate is increased, passes through a shear-thickening region before exhibiting a sharp decrease in viscosity. The latter fluids exhibit significant thixotropy, which is shown to depend on the delay time between measurements and on the composition of the fluids. Models based on electrostatically driven interactions between two oppositely charged polyelectrolytes poorly matched in terms of size, rigidity, and charge density are proposed to account for the unusual rheological behavior of the polyelectrolyte complexes under study.

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 score0.075
Threshold uncertainty score0.856

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)0.0010.000

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 head0.032
GPT teacher head0.279
Teacher spread0.247 · 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

Citations22
Published2001
Admission routes1
Has abstractyes

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