A facile dip-coating process for preparing highly durable superhydrophobic surface with multi-scale structures on paint films
Bibliographic record
Abstract
Superhydrophobic surfaces with multi-scale nano/microstructures have been prepared on epoxy paint surfaces using a feasible dip-coating process. The microstructures with 5–10 µm protuberances were first prepared on epoxy paint surface by sandblast. Then the nanostructures were introduced on the microstructure surface by anchoring 50–100 nm SiO₂ particles (nano-SiO₂) onto the sandblasted paint surface, which was completed by dip-coating with a nano-SiO₂/epoxy adhesive solution (M1). At last the surface was further modified for enhancing hydrophobicity by another dip-coating with a solution of a low surface energy polymer, aminopropyl terminated polydimethylsiloxane (ATPS) modified epoxy adhesive (M2). The water contact angle of the as-prepared samples reached as high as 167.8° and the sliding angle was 7°. The prepared superhydrophobic surface exhibited excellent durability to the high speed scouring test and high stability in neutral and basic aqueous solutions and some common organic solvents. In addition, this method can be adopted to fabricate large scale samples with a good homogeneity of the whole surface at very low cost.
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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 | 0.000 | 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) | 0.000 | 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".