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Record W2042648095 · doi:10.1021/la102605g

Computation of Contact Lines on Randomly Heterogeneous Surfaces

2010· article· en· W2042648095 on OpenAlexaff
Robert David, A. W. Neumann

Bibliographic record

VenueLangmuir · 2010
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsCanada Research ChairsUniversity of Toronto
Fundersnot available
KeywordsWettingContact angleHysteresisSolid surfaceSlip (aerodynamics)HomogeneousComputationSurface energyMaterials scienceWetting transitionSurface (topology)Range (aeronautics)Chemical physicsChemistryGeometryStatistical physicsComposite materialThermodynamicsPhysicsCondensed matter physicsMathematics

Abstract

fetched live from OpenAlex

Liquid wetting on real solid surfaces is significantly more complex than it is on the idealized surfaces of Young's equation. In the case of chemically heterogeneous solid surfaces, simulations of wetting have been carried out only for regularly patterned or one-dimensional surfaces. We describe a computational method for calculating advancing and receding contact lines on two-dimensional solid surfaces with arbitrary patterns of chemical heterogeneity. Results are verified against analytical solutions for homogeneous, single-defect, and striped surfaces. More practical surfaces with randomly placed high energy defects are also modeled. Realistic scatter in the contact angles as well as contact angle hysteresis and stick-slip motion are observed in the simulations. Hysteresis increases with the density of defects, but less so at high densities. The method allows prediction of wetting behavior from surface chemistry for a wide range of heterogeneous surfaces.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.282

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 head0.236
Teacher spread0.227 · 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

Citations18
Published2010
Admission routes1
Has abstractyes

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