Functional and versatile superhydrophobic coatings via stoichiometric silanization
Bibliographic record
Abstract
Superhydrophobic coatings have tremendous potential for applications in different fields and have been achieved commonly by increasing nanoscale roughness and lowering surface tension. Limited by the availability of either ideal nano-structural templates or simple fabrication procedures, the search of superhydrophobic coatings that are easy to manufacture and are robust in real-life applications remains challenging for both academia and industry. Herein, we report an unconventional protocol based on a single-step, stoichiometrically controlled reaction of long-chain organosilanes with water, which creates micro- to nano-scale hierarchical siloxane aggregates dispersible in industrial solvents (as the coating mixture). Excellent superhydrophobicity (ultrahigh water contact angle >170° and ultralow sliding angle <1°) has been attained on solid materials of various compositions and dimensions, by simply dipping into or spraying with the coating mixture. It has been demonstrated that these complete waterproof coatings hold excellent properties in terms of cost, scalability, robustness, and particularly the capability of encapsulating other functional materials (e.g. luminescent dyes).
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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) | 0.000 | 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 | 0.001 |
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".