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Record W2024086400 · doi:10.1142/s1758825110000433

AN ALTERNATIVE EXPLANATION OF THE EFFECT OF HUMIDITY IN GECKO ADHESION: STIFFNESS REDUCTION ENHANCES ADHESION ON A ROUGH SURFACE

2010· article· en· W2024086400 on OpenAlexafffund
Bin Chen, Huajian Gao

Bibliographic record

VenueInternational Journal of Applied Mechanics · 2010
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGeckoAdhesionStiffnessHumidityMaterials scienceRelative humidityComposite materialReduction (mathematics)GeometryPhysicsMathematicsThermodynamicsEcologyBiology

Abstract

fetched live from OpenAlex

The present study is motivated by two classes of seemingly contradicting experiments on the effect of humidity on adhesion. While one class of experiments suggests strong effect of humidity in gecko adhesion, those on micromachined surfaces indicate that the adhesion energy remains constant up to a relative humidity of 60–70% even for hydrophilic surfaces. To resolve this apparent paradox, we perform numerical simulations of the vertical peeling of a spatula pad adhered to a rough surface with periodic attachment sites. It is found that the reduction in material stiffness, which could be induced by moisture, leads to substantial increases in the pull-off force of the spatula pad, thereby providing a feasible explanation of the experimental observations.

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)0.001
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 score0.101
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.008
GPT teacher head0.259
Teacher spread0.251 · 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

Citations29
Published2010
Admission routes2
Has abstractyes

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