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Record W4388729828 · doi:10.1063/5.0168137

A new instrument for interfacial dilational rheology

2023· article· en· W4388729828 on OpenAlexafffund
Yun-Han Huang, John M. Frostad

Bibliographic record

VenueReview of Scientific Instruments · 2023
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversity of British Columbia
FundersBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsRheologyMaterials scienceMechanicsComposite materialPhysics

Abstract

fetched live from OpenAlex

We present a new design for an interfacial dilational rheometer that can generate oscillatory dilational strain on a planar air-liquid interface. The strain is generated by a pneumatic mechanism involving a deformable film, which forms a circular barrier that can contract or expand under different pressures. The interfacial stress is measured using a Wilhelmy rod. We carefully examine and demonstrate the effects of potential sources of measurement error, including inertia, drag, buoyancy, flow from the bulk phase, and surface waves. The design avoids mixed deformations present in other instruments and is currently capable of accurate measurements at frequencies up to ∼0.1 Hz and dilational strains below 0.001, with potential for higher frequencies after further theoretical development. We demonstrate the integration of the interfacial dilational rheometer with a Langmuir trough by measuring the compression isotherm of an insoluble surfactant, stearic acid. Furthermore, we verify the capability of the interfacial dilational rheometer to perform frequency and amplitude sweeps and present the storage and loss moduli for a water-soluble surfactant, sodium dodecylbenzenesulfonate, at different concentrations.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score0.441

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 head0.026
GPT teacher head0.285
Teacher spread0.259 · 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 designSimulation or modeling
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
Published2023
Admission routes2
Has abstractyes

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