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Record W2518006878 · doi:10.1002/elps.201600310

Fabrication and electrokinetic motion of electrically anisotropic Janus droplets in microchannels

2016· article· en· W2518006878 on OpenAlexafffund
Mengqi Li, Dongqing Li

Bibliographic record

VenueElectrophoresis · 2016
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsJanus particlesMicrochannelJanusElectrokinetic phenomenaMaterials scienceFabricationNanoparticleNanotechnologyElectric fieldOil dropletChemistry

Abstract

fetched live from OpenAlex

This paper presents experimental investigations of the fabrication and the motion of electrically anisotropic Janus droplets in a microchannel under externally applied direct current (DC) electrical field. The fabrication method of the Janus droplets is presented first. To begin, oil droplets are coated uniformly with positively charged nanoparticles in the aluminum oxide nanoparticle suspension. The electrically anisotropic Janus droplets are formed when the nanoparticles are accumulated to one side of the droplets in response to externally applied DC electric field. The surface coverage of the Janus droplets by nanoparticles can be adjusted by controlling the concentration of the nanoparticle suspension. The flow fields around the Janus droplets moving in a microchannel were observed with tracing particles. Finally, the electrokinetic velocity of the Janus droplets in a microchannel was measured. The effects of the strength of the electrical field, the surface coverage of the Janus droplets by nanoparticles, the size of the droplets as well as the electrolyte concentration on the electrokinetic velocity of the Janus droplets were studied.

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 score0.409
Threshold uncertainty score0.489

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 head0.005
GPT teacher head0.194
Teacher spread0.190 · 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

Citations18
Published2016
Admission routes2
Has abstractyes

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