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Record W2043382519 · doi:10.1021/la026511b

Combining Rule for Molecular Interactions Derived from Macroscopic Contact Angles and Solid−Liquid Adhesion Patterns

2003· article· en· W2043382519 on OpenAlexafffund
Junfeng Zhang, Daniel Y. Kwok

Bibliographic record

VenueLangmuir · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
Keywordsvan der Waals forceAdhesionContact angleSolid surfaceIntermolecular forceMolecular dynamicsWettingChemistryChemical physicsStatistical physicsThermodynamicsPhysicsMoleculeComputational chemistry

Abstract

fetched live from OpenAlex

We have examined a combining rule for intermolecular potentials recently proposed by Kwok et al. [ J. Phys. Chem. B 2000, 104, 741] for the calculation of solid−liquid adhesion patterns using a van der Waals model with a mean-field approximation. We found good agreement between the predicted and experimental adhesion patterns. We have also employed the 9:3, Steele's, and 12:6 combining rules for comparison purposes and found that they can also predict the general adhesion and contact angle patterns observed experimentally, but with more scatter and less detail. Results suggest that macroscopic contact angle and adhesion findings can be used to infer relationships of unlike solid−fluid interactions at a molecular level.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.295
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2003
Admission routes2
Has abstractyes

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