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Record W2034934690 · doi:10.1039/c5lc00247h

A fast and switchable microfluidic mixer based on ultrasound-induced vaporization of perfluorocarbon

2015· article· en· W2034934690 on OpenAlexaff
Marine Bézagu, Stellios Arseniyadis, Janine Cossy, Olivier Couture, Mickaël Tanter, Fabrice Monti, Patrick Tabeling

Bibliographic record

VenueLab on a Chip · 2015
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsCanadian Nautical Research Society
FundersAgence Nationale de la Recherche
KeywordsVaporizationMicrofluidicsMixing (physics)UltrasoundTransducerMaterials sciencePhase (matter)Biomedical engineeringNanotechnologyChemistryAcousticsEngineeringPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Mixing two fluids together within a microfluidic device still remains a challenging operation today. In order to achieve this goal, a number of effective micromixers have been developed over the years based on the use of either passive or active systems. Typically, passive mixers require no external energy, are more robust, and are easy to manufacture albeit they are poorly flexible. Active mixers, on the other hand, rely on external disturbance and are thus more difficult to use but are proven to have greater efficacy. Here, we report a particularly effective, remotely induced and switchable microfluidic mixer, which relies on the concomitant use of ultrasound and a perfluorocarbon (PFC) phase, with the latter benefiting from its immiscibility with most fluids and its low boiling point. More specifically, our approach is based on localized vaporization of a PFC phase at the focal zone of a transducer leading to efficient mixing of two adjacent fluids. The results show that mixing occurs ~100 ms following the delivery of the acoustic pulse, while a laminar flow is re-established on roughly the same time scale. Overall, this method is simple and effective, does not require tailored channel geometries, is compatible with both hydrophilic and hydrophobic microfluidic systems, and is applicable to a wide range of Reynolds numbers (10(-4) < Re < 2.10(0)), and the PFC phase can be easily separated from the mixed phase at the end of the run.

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 score0.011
Threshold uncertainty score0.589

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 head0.011
GPT teacher head0.201
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

Citations19
Published2015
Admission routes1
Has abstractyes

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