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Record W4410022253 · doi:10.1088/1361-665x/add3df

Active superhydrophobic surfaces with switchable wettability: a review

2025· review· en· W4410022253 on OpenAlexfundno aff
Kayah St. Germain, Yu-Chen Sun, Hani E. Naguib

Bibliographic record

VenueSmart Materials and Structures · 2025
Typereview
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWettingMaterials scienceContact angleNanotechnologyComposite material

Abstract

fetched live from OpenAlex

Abstract Surfaces science is a complex subject that is exceedingly important to understand, with mastering surface wettability leading to a new realm of applications with wide reaching impacts. Research into superhydrophobic surface is of increasing interest because of the unique abilities that these surfaces possess such as high contact angle (CA), low or high CA hysteresis (CAH), and air layer retention, among others. Furthermore, the ability to modify surfaces to control their behaviour could lead to the creation of novel devices and expand opportunities. This review paper explores the intersection between superhydrophobic surfaces and smart materials that enables the development of active superhydrophobic surfaces with switchable wettability. Active superhydrophobic surfaces have shown to be particularly well suited for use across many industries, including environmental, biomedical, and microfluidic, where their diverse range of abilities and fabrication options can be taken advantage of to provide innovative solutions to complex problems. Additionally, we explore natural occurrences of superhydrophobic surfaces, fundamental principles, fabrication techniques, and current advancements, along with their real-world applications.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.944
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.290
Teacher spread0.268 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2025
Admission routes1
Has abstractyes

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