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Record W2943851639 · doi:10.1002/adfm.201901998

Inertial Microfluidics with Integrated Vortex Generators Using Liquid Metal Droplets as Fugitive Ink

2019· article· en· W2943851639 on OpenAlexfundno aff
Ngan Nguyen, Peter Thurgood, Aram Arash, Elena Pirogova, Sara Baratchi, Khashayar Khoshmanesh

Bibliographic record

VenueAdvanced Functional Materials · 2019
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsnot available
FundersRMIT UniversityAustralian Research CouncilOntario Ministry of Natural Resources and ForestryAdobe Systems
KeywordsMaterials scienceMicrofluidicsPolydimethylsiloxaneVortexLiquid metalFabricationFluidicsNanotechnologyScrollPolystyreneComposite materialMechanicsMechanical engineeringAerospace engineering

Abstract

fetched live from OpenAlex

Abstract This work demonstrates a simple method for fabricating nearly spherical dome structures on top of lithographically defined microfluidic channels using gallium‐based liquid metal droplets as fugitive ink. The droplets remain stable during the pouring and curing of polydimethylsiloxane and can be easily removed by applying a basic solution. This facilitates the formation of domes with diameters of a few hundred micrometers patterned on the desired locations of the channel. The expansion of the channel at the interface of the dome leads to formation of a large vortex inside the dome. Experiments using high‐speed imaging along with numerical simulations show the utility of the vortex‐induced flow rotation for orbiting of human monocytes and polystyrene microbeads inside the dome. The lateral displacement of liquids caused by the vortex is further utilized for creating controllable multiband flow/color profiles within a T‐mixer. The method enables the fabrication of customized, complex, and 3D microfluidic systems utilizing planar microfabricated structures.

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: Empirical
Teacher disagreement score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.007
GPT teacher head0.187
Teacher spread0.179 · 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

Citations31
Published2019
Admission routes1
Has abstractyes

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