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Record W2745151459 · doi:10.1122/1.4996843

Modeling the intrinsic viscosity of polydisperse disks

2017· article· en· W2745151459 on OpenAlexaff
Issam Ismail, Jeremy Vandenberg, Ahmed Abdala, C. W. Macosko

Bibliographic record

VenueJournal of Rheology · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversity of Waterloo
FundersUniversity of MinnesotaKhalifa University of Science, Technology and ResearchAbu Dhabi National Oil CompanyUtah Agricultural Experiment Station
KeywordsRheologyShear rateLog-normal distributionPéclet numberShear flowMaterials scienceViscosityDispersityThermodynamicsStatistical physicsMechanicsPhysicsMathematicsStatisticsPolymer chemistry

Abstract

fetched live from OpenAlex

In this work, we model the rheology of dilute colloidal oblate spheroids in their high aspect ratio limit of circular disks. Theoretical models for the intrinsic viscosity, [η], of disks in shear flow are reviewed: The shear-independent, monodisperse Kuhn-Kuhn model, its polydisperse form by van der Kooij, and the shear-dependent models of Stewart and Sorenson, Leal and Hinch, and Brenner. Based on these previous works, three analytical models are introduced to describe the shear response over the entire range of practically accessible rotational Peclet numbers (Pe) and aspect ratios. Using the fact that [η] is linearly additive for sufficiently dilute systems we derive a general expression for polydisperse disks as a function of the two independent variables of particle diameter D and thickness t, that is, assuming D and t to be uncorrelated independent variables. We then argue for continuum modeling being preferable to discrete for using rheological measurements to estimate particle size distribution parameters. Computational results are shown for the continuum model in shear flow and generalized to uniaxial and planar extension, as well as to different particle distributions such as lognormal, normal, and bimodal. Finally, a modified form of [η], which we describe as innate viscosity (η), is suggested as an alternative method of modeling rheology of dilute dispersions.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.017
GPT teacher head0.266
Teacher spread0.249 · 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 designSimulation or modeling
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

Citations4
Published2017
Admission routes1
Has abstractyes

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