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Record W2467927299 · doi:10.1177/0954405415615801

Microfluidic device fabrication with serigraphy technique

2015· article· en· W2467927299 on OpenAlexaff
Vahé Nerguizian, Anas Alazzam, Jules Gauthier, Dacian Roman, Ion Stiharu, Miguel N. Burnier

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · 2015
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsMcGill UniversityPolytechnique MontréalConcordia UniversityÉcole de Technologie Supérieure
Fundersnot available
KeywordsFabricationMicrofluidicsPhotoresistDielectrophoresisSilicone rubberMaterials scienceNanotechnologyPolystyreneCharacterization (materials science)MicrofabricationSiliconeGasketPolymerComposite material

Abstract

fetched live from OpenAlex

This article provides the design and fabrication details of a new technique to build a microfluidic device with two parallel substrates and a silicone gasket. The fabrication process uses screen printing technology offering fast and low-cost microdevices without the need for high-cost fabrication equipment and special photoresist processes. Hermetic microfluidic channels of 300 µm width and 50 µm height having parallel facing electrodes on two substrates are made with simple serigraphy technique using silicone rubber. The fabricated devices were experimentally tested for detection and characterization of polystyrene particles and living cells by negative and positive dielectrophoresis. The reported technique enables simple manipulation, centering, detection and characterization of living cells at low and high frequencies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.012
GPT teacher head0.190
Teacher spread0.178 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations4
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part B Journal of Engineering ManufactureSame topicMicrofluidic and Bio-sensing TechnologiesFrench-language works237,207