Producing a superhydrophobic paper and altering its repellency through ink-jet printing
Bibliographic record
Abstract
A new method for making superhydrophobic (SH) paper based on spraying a nanocomposite film is developed. Furthermore, manipulating the wetting characteristics of SH paper has been demonstrated through a new method, i.e. printing solid grey patterns of different intensities with simple printing technology (home or office grade ink-jet and laser printers). It has been found that for a range of ink intensities (0-85%), water drop mobility can be changed at a different rate (almost independently) from repellency. The repellency of water decreases minimally up to 85% ink intensity with a sharp decrease up to 100% ink intensity. Drop mobility remains constant up to 30% ink intensity with a steady decrease up to 100% ink intensity. It was observed that using ink-jet or laser printing would yield different results for the change of mobility or repellency with higher amounts of ink/toner used. Being able to achieve almost independent control of water drop mobility over water drop repellency on SH paper would allow inexpensive lab-on-paper devices to be used for sampling, mixing and transport of liquids.
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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 | 0.001 |
| 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".