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Record W2169854510 · doi:10.1098/rspa.2010.0015

Impact of drops of surfactant solutions on small targets

2010· article· en· W2169854510 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.

Bibliographic record

VenueProceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 2010
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsAdler
Fundersnot available
KeywordsLamella (surface anatomy)Pulmonary surfactantNucleationMaterials scienceInstabilityChemical engineeringComposite materialChemistryMechanicsPhysics

Abstract

fetched live from OpenAlex

The collisions of drops of surfactant solutions (dioctyl sulfosuccinate sodium salt (DOS) and trisiloxane oxypropylene polyoxyethylene (Silwett L77)) with small disc-like targets were studied both experimentally and theoretically. Upon impact, the drops spread very fast beyond the target in the shape of a thin lamella surrounded by a thick rim. No significant difference between water and surfactant solutions was observed in the early stage of the impact. But the collapse stages were very different. In particular, the lamellas of solutions of Silwett L77 disintegrated owing to a spontaneous nucleation of holes, giving to the lamella a web-like structure prior to its break-up. In contrast, lamellas of DOS solutions collapsed like water lamellas, except that the maximum diameter and the lifetime of the lamella of the most concentrated DOS solution were significantly increased compared with pure water and other surfactant solutions. A theoretical analysis shows that the observed instability effects in the lamella and the increase in the size and lifetime of the lamella can be caused by the coupling between liquid inertia and Marangoni stresses.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.899
Threshold uncertainty score0.275

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 head0.009
GPT teacher head0.208
Teacher spread0.198 · 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