Unexpected Superhydrophobicity on a Wide Range of Substrates via a One-step Immersion in Aqueous Solution without Hydrophobic Agent
Bibliographic record
Abstract
Superhydrophobic surfaces were unexpectedly constructed by immersing a variety of substrates (aluminum sheet, melamine sponge, cotton fabric, and wood) into an aqueous solution containing tea polyphenols and metal ions (Fe2+, Ag+, Ce3+) and the potential applications in corrosion resistance for superhydrophobic aluminum, water absorption resistance for superhydrophobic wood, oil/water separation for superhydrophobic sponge and self-cleaning for superhydrophobic fabric were investigated. Superhydrophobic surfaces were unexpectedly constructed by immersing substrates into an aqueous solution containing tea polyphenols (TP) and metal ions. Metal ions were chelated with TP to generate rough surface structures and reduced to metal particles, which were active to anchor the carbon contamination from the atmosphere. Superhydrophobicity was unexpectedly achieved by the joint effect of surface roughness and surface carbon contamination.
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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 | 0.000 |
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 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".