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Record W2136307263 · doi:10.1115/imece2007-42213

Whole Chip Temperature Measurements Using Thin-Film PDMS/Rhodamine B for Microfluidic Chip Design

2007· article· en· W2136307263 on OpenAlexaff
Razim Samy, Tomasz Glawdel, Carolyn L. Ren

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMicrochannelMaterials scienceRhodamine BJoule heatingMicrofluidicsTemperature measurementOptoelectronicsThin filmSiliconComposite materialNanotechnologyChemistry

Abstract

fetched live from OpenAlex

A novel method for in-situ temperature measurements of microfluidic devices using thin-film poly(dimethylsiloxane) (PDMS) saturated with Rhodamine B dye is reported. Rhodamine B is commonly injected into the working fluid for on-chip temperature field visualization of glass and silicon based microfluidic devices since its fluorescent intensity is temperature dependent. However, such a visualization method results in unreliable temperature measurements for polymeric devices such as PDMS due to high absorption and adsorption. Thus, an inexpensive temperature measurement technique was developed in which a thin PDMS layer (∼30 μm) is fabricated and submersed for several days into a Rhodamine B solution. To prevent backward diffusion of the dye into the working fluid during operation, a glass barrier (∼150 μm) is bonded between the thin film and the PDMS mold containing the microchannel design. Temperature measurements are made by utilizing standard method of measuring changes in the normalized fluorescent intensity. For verification purposes, a new calibration curve is developed and the thin film is tested with a tapered microchannel subjected to joule heating. The resulting temperature field along the axial direction of the channel for different input power compares well with numerical simulations. Errors in temperature measurement due to the current design are discussed.

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)0.001
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: none
Teacher disagreement score0.852
Threshold uncertainty score0.778

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.050
GPT teacher head0.255
Teacher spread0.206 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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