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Record W2004530722 · doi:10.1021/jp026676t

Calculation of Solid−Liquid Work of Adhesion Patterns from Combining Rules for Intermolecular Potentials

2002· article· en· W2004530722 on OpenAlexafffund
Junfeng Zhang, Daniel Y. Kwok

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2002
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAdhesionContact angleSurface tensionSolid surfaceWork (physics)Intermolecular forceYield (engineering)Materials scienceThermodynamicsSurface (topology)WettingChemical physicsChemistryMathematicsPhysicsComposite materialGeometryMoleculeOrganic chemistry

Abstract

fetched live from OpenAlex

The thermodynamic work of solid−liquid adhesion is a well-defined property. Their phenomenological patterns relating to surface tensions, however, have not been well-characterized. We employed a hard sphere model to determine the solid−liquid work of adhesion patterns from a mean-field theory through calculations of the liquid−vapor, solid−vapor, and solid−liquid interfacial tensions. By plotting the work of adhesion with the liquid−vapor interfacial tension, we constructed curves that appear to behave in a very regular manner for a variety of combining rules; the curves shift regularly when we increase the strength of solid−solid interaction and hence the solid−vapor surface tension. Contact angle patterns were also constructed via Young's equation. We found that, except Berthelot's rule, the (9:3), Steele, and (12:6) combining rules yield essentially similar adhesion patterns. The regularity of the patterns is remarkable and in reasonable agreement with recent experimental findings. We have shown that macroscopic experimental adhesion and contact angle patterns can, in principle, be reproduced from consideration of only intermolecular forces. The exact patterns depend on the choice of the combining rules.

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 score0.026
Threshold uncertainty score0.284

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 head0.014
GPT teacher head0.240
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

Citations20
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry BSame topicAdhesion, Friction, and Surface InteractionsFrench-language works237,207