Plant-based, aqueous, water-repellent sprays for coating textiles
Bibliographic record
Abstract
Novel superhydrophobic coatings, that are both biodegradable and biosourced, have the potential to revolutionize the water-repellent coating industry. Here, water-repellent coatings were prepared from commercially unavailable plant waxes, isolated using solvent extraction and characterized using DSC, GC-MS and DLS. In the first stage, a plant survey was conducted to identify an ideal plant source for the final spray, in which Whatman filter paper was submerged in a wax-solvent solution with recrystallization occurring upon air-drying. In the second stage, aqueous, PFC-free wax dispersions were prepared, coated onto textiles (cotton and polyester), and heat-treated with a home drying machine to allow for the spreading and recrystallization of the waxes. In both stages, SEM visualization verified the coating's morphology, and contact angle measurements showed them to be superhydrophobic. It was concluded that, using less coating material than commercial coatings, high-performing petroleum-free coatings could be made and applied onto textiles of various polarities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".