Active superhydrophobic surfaces with switchable wettability: a review
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".