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Record W2017219794 · doi:10.1063/1.3514138

A total internal reflection fluorescence microscopy study of mass diffusion enhancement in water-based alumina nanofluids

2010· article· en· W2017219794 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Applied Physics · 2010
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsRhodamine 6GThermal diffusivityNanofluidTotal internal reflection fluorescence microscopeDiffusionAnalytical Chemistry (journal)ChemistryMass diffusivityMicroscopyDispersion (optics)NanoparticleMaterials scienceFluorescenceOpticsNanotechnologyThermodynamicsChromatographyPhysics

Abstract

fetched live from OpenAlex

Mass diffusion of rhodamine 6G (R6G) in water-based alumina nanofluids is studied by means of total internal reflection fluorescence (TIRF) microscopy. We report a mass diffusivity enhancement that reaches an order of magnitude in a 2 vol % nanofluid when compared to the value in deionized water. Since experiments were performed with positively charged R6G, interfacial complexation between the dye and the nanoparticles was not observed. The effect of local density variations on mass diffusivity measurements is also addressed. An explanation for the enhancement of mass diffusion is presented using arguments based on dispersion, and it is shown that it correctly describes the order of magnitude differences between the thermal conductivity and mass diffusivity enhancements reported in the literature.

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.

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 score0.015
Threshold uncertainty score0.512

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 head0.007
GPT teacher head0.235
Teacher spread0.228 · 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