Superhydrophobic wonders: A comprehensive review of nanomaterial-based surfaces and their myriad applications
Bibliographic record
Abstract
Superhydrophobic surfaces (SHSs) exhibit exceptional water repellency characterized by a high contact angle (>150°), extremely low surface energy, and minimal sliding angle (<5°). They demonstrate minimal contact angle hysteresis (<10°) and excellent Cassie-Baxter state stability. These properties, attributed to the surface's unique micro- and nano-structures or tailored chemical composition, induce a non-wetting behavior. SHSs hold significant promise for a wide range of applications due to their captivating functionalities, including efficient oil-water separation, drag reduction, anti-fogging, anti-biofouling, self-cleaning capabilities, and more. Their inherent durability and diverse functionalities render them attractive for various commercial and everyday applications. This review provides a comprehensive overview of the materials and fabrication processes employed to create SHSs, encompassing micro- and nano-structuring techniques, chemical modification strategies, and superhydrophobic coating deposition methods. We further delve into the extensive and multifaceted applications of SHSs across the transportation, energy, and biomedical engineering sectors. Despite their demonstrated potential, challenges persist in the development and practical implementation of SHSs. addressing these challenges necessitates continued research and innovation. This review aims to stimulate further progress in the field by identifying potential future research directions and unlocking the full potential of SHSs for groundbreaking applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".