MétaCan
Menu
Back to cohort
Record W4410048146 · doi:10.51200/susten.v2i1.5052

Ultrahydrophobic Surface for Water Treatment by Membrane Processes-Prediction of Water Contact Angle on Air/Solid Composite Surface by Solving Young-Laplace Equation

2025· article· en· W4410048146 on OpenAlexaff
Takeshi Matsuura

Bibliographic record

VenueSustainable Engineering · 2025
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsContact angleLaplace transformLaplace's equationSurface (topology)Composite numberSolid surfaceMaterials scienceMembraneMechanicsComposite materialMathematical analysisMathematicsGeometryPhysicsChemistryPartial differential equationChemical physics

Abstract

fetched live from OpenAlex

The evaluation of contact angle (CA) of air-solid composite surface is growing in its importance in membrane separation technology. The reason is that the super-hydrophobic property of the surface allows self-cleaning of membrane surface in various membrane separation processes and also mitigates pore wetting, which is considered the serious disadvantage of membrane distillation. The Cassie-Baxter equation is currently considered one of the best tools to evaluate CA of the air-solid composite surface. However, most of the experimental works of CA measurement were carried out by the sessile drop method, in which the size of the droplet is limited to micro- or submicrometer range, and it is not known how CA is affected by the air content of the air-solid composite surface especially when the droplet size is in a range of millimeter. In this work, the meniscus shape of a large water droplet with a size greater than the capillary length (2.713 mm) was calculated for different air contents at the air-solid surface by solving the Young-Laplace differential equation. It was concluded that the effect of fs (fraction of solid surface) on CA does not depend significantly on the droplet size, even though the droplet flattens considerably as the droplet size increases.

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 categoriesMeta-epidemiology (narrow)
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 score0.231
Threshold uncertainty score1.000

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 integrity0.0000.000
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 head0.008
GPT teacher head0.220
Teacher spread0.212 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueSustainable EngineeringSame topicSurface Modification and SuperhydrophobicityFrench-language works237,207