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Record W2073904186 · doi:10.1063/1.4756914

Direct current pulse train actuation to enhance droplet control in digital microfluidics

2012· article· en· W2073904186 on OpenAlexaff
Miguel Angel Murran, Homayoun Najjaran

Bibliographic record

VenueApplied Physics Letters · 2012
Typearticle
Languageen
FieldEngineering
TopicElectrowetting and Microfluidic Technologies
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsMicrofluidicsDigital microfluidicsOvershoot (microwave communication)Pulse-width modulationPulse (music)Materials scienceDigital controlPosition (finance)Displacement (psychology)NanotechnologyElectronic engineeringOptoelectronicsEngineeringElectrical engineeringElectrowettingVoltage

Abstract

fetched live from OpenAlex

The effective operation of a digital microfluidic (DMF) device depends on its ability to actuate droplets. Pulse width modulation of actuating signals (DC pulse train actuation) is proposed as a practical digital implementation and enhanced droplet manipulation technique. Experimental and simulation results demonstrate the efficacy of droplet incremental displacement and velocity control by modulating the width of each actuation pulse. This will in turn enable the control of the non-linear droplet transport dynamics to minimize droplet position overshoot, deformation, and fragmentation. As a result, DCPT actuation offers unparalleled control over droplet position and speed in DMF devices.

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 score0.157
Threshold uncertainty score0.907

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 head0.006
GPT teacher head0.215
Teacher spread0.209 · 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

Citations12
Published2012
Admission routes1
Has abstractyes

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