Preparation of large‐scale, durable, superhydrophobic PTFE films using rough glass templates
Bibliographic record
Abstract
Large superhydrophobic polytetrafluoroethylene (PTFE) films, with good durability, were successfully prepared by a facile, low cost, environmentally friendly templating method, using a PTFE emulsion. For the first time, commercially available rough glass was employed as a reusable template. The results show that both the microstructure of the glass template and the concentration of the PTFE emulsion play important roles in the superhydrophobicity of the films. Commercially available, acid‐etched, rough glass is found to be an ideal template for such films, the superhydrophobicity increasing with decreasing emulsion concentration. Abrasive wear testing shows that superhydrophobic PTFE film, prepared under an optimal concentration of 5 wt% PTFE emulsion, has good abrasion resistance. Moreover, the results show that this method is suitable for the large‐scale preparation of superhydrophobic PTFE films. Copyright © 2017 John Wiley & Sons, Ltd.
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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".