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Record W2162315550 · doi:10.1071/ch05136

Marangoni Effects in Liquid Jets of Non-Ionic Surfactants

2005· article· en· W2162315550 on OpenAlexaff
Daniel M. Colegate, Colin D. Bain

Bibliographic record

VenueAustralian Journal of Chemistry · 2005
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsSKiN Health
FundersEngineering and Physical Sciences Research CouncilDirectorate for Mathematical and Physical SciencesUniversity of Oxford
KeywordsChemistrySurface tensionAdsorptionDiffusionMarangoni effectPulmonary surfactantCritical micelle concentrationEllipsometryIonic liquidAnalytical Chemistry (journal)ThermodynamicsMicellePhysical chemistryChromatographyOrganic chemistryMaterials scienceAqueous solutionNanotechnologyCatalysisThin film

Abstract

fetched live from OpenAlex

The adsorption of nonionic surfactants in the CnE8 family at the air–water interface has been studied on the millisecond timescale in a free liquid jet. The amount of adsorbed surfactant was measured by ellipsometry. The rates of adsorption are compared with a diffusion-controlled adsorption model. In the case of C10E8, which is below its cmc, the monomer diffusion coefficient provides a good fit to the experimental data. For n = 12, 14, and 16, micelles control the mass transport. The best fit diffusion coefficients are close to, but not identical with, the literature values for the micellar diffusion coefficients. Laser Doppler velocimetry was used to measure the change in surface velocity arising from adsorption of the surfactant, for n = 12, 14, and 16. There was a qualitative correlation between the retardation of the surface velocity and the surface tension gradients.

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)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.247
Teacher spread0.238 · 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
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

Citations4
Published2005
Admission routes1
Has abstractyes

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Same venueAustralian Journal of ChemistrySame topicSurfactants and Colloidal SystemsFrench-language works237,207