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Nanoscale Flow on a Bubble Mattress: Effect of Surface Elasticity

2008· article· en· W2006482413 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

VenuePhysical Review Letters · 2008
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsCanadian Nautical Research Society
Fundersnot available
KeywordsElasticity (physics)BubbleSlippageMechanicsMaterials scienceNanoscopic scaleStiffnessSurface forceSurface forces apparatusClassical mechanicsNanotechnologyAtomic force microscopyComposite materialPhysics

Abstract

fetched live from OpenAlex

We present an experimental study of the elastic properties of a superhydrophobic surface in the Cassie regime, due to the gas bubbles trapped at the liquid-solid interface. We use a surface force apparatus to measure the force response to an oscillating drainage flow between a sphere and the surface. We show that the force response allows to determine the surface elasticity without contact, using the liquid film as a probe. The elasticity of the bubble mattress is dominated by the meniscii stiffness, and its determination enables us to probe the shape of these meniscii. Another effect of surface elasticity is to decrease the viscous friction. We show that this effect can be wrongly attributed to rate dependant boundary slippage if elastohydrodynamics is not taken into account.

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 categoriesInsufficient payload (model declined to judge)
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 score0.005
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.001

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 head0.020
GPT teacher head0.274
Teacher spread0.255 · 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