Fabrication of Superamphiphobic Surfaces via Spray Coating; a Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it