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Record W1988241975 · doi:10.1103/physreve.84.011922

Dielectric response of particles in flowing media: The effect of shear-induced rotation on the variation in particle polarizability

2011· article· en· W1988241975 on OpenAlexafffund
Marija Nikolic‐Jaric, Graham A. Ferrier, D. J. Thomson, Greg E. Bridges, M. R. Freeman

Bibliographic record

VenuePhysical Review E · 2011
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsUniversity of ManitobaResearch Manitoba
FundersCanadian Institutes of Health Research
KeywordsAnisotropyPopulationElectric fieldRotational symmetryDielectricPolarizabilityMechanicsParticle (ecology)Polarization (electrochemistry)PhysicsMaterials scienceShear flowShear (geology)Classical mechanicsOpticsChemistryComposite materialQuantum mechanics

Abstract

fetched live from OpenAlex

When particles in liquid suspensions flow through channels and pipes in a laminar fashion, the resulting parabolic velocity profile gives rise to shear, which induces the particles to rotate. If flowing suspensions containing dielectric particles are immersed in an external electric field, the anisotropic polarization induced in rotating nonspherical particles will vary with the orientation of the particle with respect to the external field; what results is an uncertainty in experimental measurements that involve particle polarization. The present study establishes the limits of this uncertainty and shows that departure from spherical symmetry in individual particles can lead to a significant overlap in measurements attempting to discriminate between particle subpopulations in suspensions. For example, the uncertainty in signal amplitude for a population of activated T-lymphocytes can be as high as 20%. Such concerns arise in applications like field-flow fractionation, dielectrophoretic sorting of particles, flow impedance measurements and cytometry, and, most recently, isodielectric separation, all of which are used to separate particles in a flow based on their dielectric response. This paper considers axisymmetric particles as the first departure from the approximation of spherical symmetry, shows how to calculate an estimate of the size of the population overlap, and suggests possible strategies to minimize it.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.155
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.026
GPT teacher head0.255
Teacher spread0.229 · 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

Citations4
Published2011
Admission routes2
Has abstractyes

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