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Record W2000671910 · doi:10.1039/b613198k

Transient surface patterns during adhesion and coalescence of thin liquid films

2006· article· en· W2000671910 on OpenAlexfundno aff
Hongbo Zeng, Boxin Zhao, Yu Tian, Matthew Tirrell, L. Gary Leal, Jacob N. Israelachvili

Bibliographic record

VenueSoft Matter · 2006
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaTsinghua UniversityNational Aeronautics and Space Administration
KeywordsCoalescence (physics)PolymerMaterials scienceRippleChemical physicsAdhesionNanotechnologyComposite materialChemistryThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Surface deformations during the coalescence of two polymer melt films were studied by use of a surface forces apparatus (SFA). Well-ordered periodic surface ripple/finger patterns were observed during the adhesion and coalescence, which eventually disappeared, leaving smooth polymer-air interfaces. The life-times of these transient well-ordered patterns depend on the viscosity and film thickness of the polymer melts. These observations are in contrast to the conventional understanding that liquid-liquid coalescence usually occurs with the deforming surfaces remaining smoothly curved at all stages, with no esoteric shape-transitions. The results reveal a new feature associated with liquid-liquid adhesion/coalescence, which may be of key importance for a full understanding of coalescence processes. We propose an explanation for the observed phenomenon in terms of simple physical concepts, and discuss other microscopic and macroscopic (including biological) systems where similar effects are likely to occur.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.492

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 head0.004
GPT teacher head0.188
Teacher spread0.184 · 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 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

Citations30
Published2006
Admission routes1
Has abstractyes

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