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Record W2324951097 · doi:10.1021/la500277n

Contact Angle Hysteresis of Non-Flattened-Top Micro/Nanostructures

2014· article· en· W2324951097 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLangmuir · 2014
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsContact angleWettingHysteresisMicrostructureMaterials scienceSurface energyNanostructureSurface (topology)Wetting transitionGibbs free energyLotus effectOpticsNanotechnologyComposite materialCondensed matter physicsChemistryThermodynamicsGeometryPhysics

Abstract

fetched live from OpenAlex

A two-dimensional (2D) thermodynamic model is proposed to predict the contact angle (CA) and contact angle hysteresis (CAH) of different types of surface geometries, particularly those with asperities having nonflattened tops. The model is evaluated by micro/nano sinusoidal and parabolic patterns fabricated by laser ablation. These microstructures are analyzed thermodynamically through the use of the Gibbs free energy to obtain the equilibrium contact angle (CA) and contact angle hysteresis (CAH). The effects of the geometrical details of two types of microstructures on maximizing the superhydrophobicity of the nanopatterned surface are also discussed in an attempt to design surfaces with desired and/or optimum wetting characteristics. The analysis of the various surfaces reveals the important geometrical parameters that may lead to the lotus effect (high CA > 150° and low CAH < 10°) or petal effect (high CA > 150° and high CAH ≫ 10°).

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.

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 score0.099
Threshold uncertainty score0.768

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)0.0010.000

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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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