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Record W2782552779 · doi:10.1039/c7ra11194k

Microfluidic flow switching <i>via</i> localized acoustic streaming controlled by surface acoustic waves

2018· article· en· W2782552779 on OpenAlexaff
Jin Ho Jung, Ghulam Destgeer, Jinsoo Park, Husnain Ahmed, Kwangseok Park, Hyung Jin Sung

Bibliographic record

VenueRSC Advances · 2018
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsKootenay Association for Science & Technology
FundersKorea Advanced Institute of Science and TechnologyNational Research Foundation of KoreaKorea Polar Research InstituteMinistry of Science, ICT and Future PlanningNational Research Foundation
KeywordsAcoustic streamingMicrofluidicsAcousticsAcoustic waveMaterials scienceSurface acoustic waveFlow (mathematics)Surface (topology)NanotechnologyPhysicsMechanicsUltrasonic sensor

Abstract

fetched live from OpenAlex

We propose an acoustic flow switching device that utilizes high-frequency surface acoustic waves (SAWs) produced by a slanted-finger interdigitated transducer. As the acoustic field induced by the SAWs was attenuated in the fluid, it produced an acoustic streaming flow in the form of a pair of symmetrical microvortices, which induced flow switching between two fluid streams in a controlled manner. The microfluidic device was composed of a piezoelectric substrate attached to a polydimethylsiloxane (PDMS) microchannel having an H-shaped junction that connected two fluid streams in the middle. The two immiscible fluids, separated by the PDMS wall, flowed in parallel, briefly came in contact at the junction, and separated again into the downstream microchannels. The acoustic streaming flow induced by the SAWs rotated the fluid streams within the microchannel cross-section, thereby altering the respective positions of the two fluids and directing them into the opposite flow paths. The characteristics of the flow switching mechanism were investigated by tuning the input voltage and the flowrates. On-demand acoustic flow switching was successfully achieved without additional moving parts inside the microchannel. This technique may be useful for fundamental studies that integrate complex experimental platforms into a single chip.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.730
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.006
GPT teacher head0.216
Teacher spread0.210 · 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.

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

Citations20
Published2018
Admission routes1
Has abstractyes

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