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Record W3004859661 · doi:10.1063/1.5142563

Rheology of sodium and zinc ionomers: Effects of neutralization and valency

2020· article· en· W3004859661 on OpenAlexafffund
Muaad Zuliki, Shiling Zhang, Kudzanai Nyamajaro, Tanja Tomković, Savvas G. Hatzikiriakos

Bibliographic record

VenuePhysics of Fluids · 2020
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRheologyReptationRheometerViscoelasticityIonic bondingExtensional viscosityZincThermodynamicsComposite materialMaterials sciencePolymer chemistryChemical engineeringPhysicsChemistryIonPolymerOrganic chemistryMetallurgyShear viscosity

Abstract

fetched live from OpenAlex

Using a parallel-plate rheometer equipped with a partitioned plate and the Sentmanat extensional rheometer fixture, a full rheological characterization of several commercial ionomers (sodium and zinc) and their corresponding parent copolymers has been carried out. Particular emphasis has been placed on the distribution of the relaxation times to identify the characteristic times, such as reptation, Rouse, and lifetime of associations that are associated with entanglements, ionic and hydrogen bonding associations. As such, scaling laws have been used to calculate the order of magnitude of these characteristic times that are important parameters to gain a better understanding of their rheological behavior. To study the effects of ionic reversible associations, the commercial ionomers were completely un-neutralized and their rheological behavior was compared directly with their associative counterparts. The rheological comparison included the linear viscoelastic moduli, the damping function, and extensional rheology, demonstrating the significant effects of ionic interactions. Moreover, the rheological properties of sodium and zinc ionomers are also compared addressing the effect of valency of ions (Na+ vs Zn++).

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 score0.015
Threshold uncertainty score0.225

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 head0.226
Teacher spread0.214 · 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

Citations17
Published2020
Admission routes2
Has abstractyes

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