Fabrication of Superamphiphobic Surfaces via Spray Coating; a Review
Bibliographic record
Abstract
Abstract Superamphiphobic coatings that simultaneously repel both water and oil and are applicable to a wide range of surfaces are needed for use in self‐cleaning, anti‐icing, and antimicrobial coatings. Spray coating is a method that can be used to apply such coatings to a wide range of surfaces in a scalable and high throughput manner. This review presents a comprehensive overview of the materials architecture, synthesis, applications, and figures‐of‐merit of superamphiphobic surfaces that are deposited using spray coating. The design requirements of superamphiphobic surfaces—surface roughness and wettability, re‐entrant topographic features, and chemical composition—are initially introduced. Based on the material, different synthesis techniques are then discussed with a focus on metal oxides and metal oxide composites, polymers, emerging, and green materials. The areas of application of superamphiphobic coatings are also presented. Finally, the main hurdles in using such coatings in real‐life applications are discussed in depth, and emerging technologies for overcoming these challenges are presented.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".