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Record W2752424799 · doi:10.1088/1361-6439/aa8b21

Printing-based fabrication method using sacrificial paper substrates for flexible and wearable microfluidic devices

2017· article· en· W2752424799 on OpenAlexafffund
Daehan Chung, Bonnie L. Gray

Bibliographic record

VenueJournal of Micromechanics and Microengineering · 2017
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaSimon Fraser University
KeywordsFabricationMicrofluidicsWearable computerNanotechnologyWearable technologyMaterials scienceComputer scienceEmbedded systemEngineeringMedicine

Abstract

fetched live from OpenAlex

Abstract We present a simple, fast, and inexpensive new printing-based fabrication process for flexible and wearable microfluidic channels and devices. Microfluidic devices are fabricated on textiles (fabric) for applications in clothing-based wearable microfluidic sensors and systems. The wearable and flexible microfluidic devices are comprised of water-insoluable screen-printable plastisol polymer. Sheets of paper are used as sacrificial substrates for multiple layers of polymer on the fabric’s surface. Microfluidic devices can be made within a short time using simple processes and inexpensive equipment that includes a laser cutter and a thermal laminator. The fabrication process is characterized to demonstrate control of microfluidic channel thickness and width. Film thickness smaller than 100 micrometers and lateral dimensions smaller than 150 micrometers are demonstrated. A flexible microfluidic mixer is also developed on fabric and successfully tested on both flat and curved surfaces at volumetric flow rates ranging from 5.5–46 ml min −1 .

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 score0.379
Threshold uncertainty score0.583

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 head0.019
GPT teacher head0.262
Teacher spread0.243 · 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

Citations5
Published2017
Admission routes2
Has abstractyes

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