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Record W1823173488 · doi:10.1002/elps.201400194

A novel particle separation method based on induced‐charge electro‐osmotic flow and polarizability of dielectric particles

2014· article· en· W1823173488 on OpenAlexafffund
Fang Zhang, Dongqing Li

Bibliographic record

VenueElectrophoresis · 2014
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolarizabilityDielectrophoresisElectric fieldParticle (ecology)DielectricElectrophoresisMaterials scienceMicrofluidicsChemical physicsFlow (mathematics)MechanicsMolecular physicsNanotechnologyChemistryPhysicsChromatographyOptoelectronicsMolecule

Abstract

fetched live from OpenAlex

A new microfluidic method of particle separation was proposed and studied theoretically in this paper. This method is based on the induced charge electro-osmotic flow (ICEOF) and polarizability of dielectric particles. In this method, a pair of metal plates is embedded on the side channel walls to create a region of circulating flows under applied electric field. When a dielectric particle enters this region, the vortices produced by ICEOF around the particle will interact with the circulating flows produced by the metal plates. Such hydrodynamic interaction influences the particle's trajectory, and may result in the particle being trapped in the flow circulating zone or passing through this flow circulating zone. Because the hydrodynamic interaction is sensitive to the applied electric field, and the polarizability and the size of the particles, separation of different particles can be realized by controlling these parameters. Comparing with electrophoresis and dielectrophoresis methods, this strategy presented in this paper is simple and sensitive.

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 score0.363
Threshold uncertainty score0.700

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.232
Teacher spread0.221 · 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

Citations16
Published2014
Admission routes2
Has abstractyes

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