Bibliographic record
Abstract
Inspired by “lotus-effect”, a superhydrophobic surface, in general, is prepared via two steps: (i) creating a surface roughness and then (ii) lowering the surface energy via a self-assembly of organic molecules or via low surface energy coatings. Superhydrophobicity cannot result if one of these two essential factors does not coexist. In the present work, it has been shown that superhydrophobic properties can be achieved on silver surfaces both via two-steps and a novel and simple one-step process. In the two step-processes a fractal-structured silver film deposited on copper surface by galvanic exchange reactions was passivated using stearic acid organic molecules to reduce the surface energy resulting in the superhydrophobicity. In the one-step process, however, the copper substrates were simply immersed in the silver nitrate solution containing fluoroalkylsilane (FAS-17) molecules resulting in superhydrophobicity. The silver films prepared both via two-steps and one-step processes were found to be highly water repellant with the water drops rolling off those surfaces. Scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) were utilized to understand the morphology, molecular bonding, and chemical properties of the superhydrophobic silver surfaces.
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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".