Facile Preparation of a Transparent and Rollable Omniphobic Coating with Exceptional Hardness and Wear Resistance
Bibliographic record
Abstract
The encapsulating film for the touchscreen of a foldable smartphone consists of a flexible polymer layer covered by a hard coating and an antismudge coating, and the two coating layers are currently deposited via separate steps. This paper reports the preparation of a bilayer bifunctional coating via the deposition of a single polymer mixture. The base material for the coating is a ladder-like polysilsesquioxane (LASQ) that is derived from the sol–gel chemistry of 2-(3,4-epoxycyclohexyl)ethyltrimethoxysilane. Reacting a limiting amount of the liquid antismudge agent FP-COOH, which is a perfluorinated poly(propylene oxide) bearing a terminal carboxyl group, with LASQ yields m -LASQ-FP, a mixture of unreacted LASQ, and a graft copolymer LASQ-FP. m -LASQ-FP at a fluorine mass fraction of 6.0% is photocured to yield a coating with a surface energy of 12.3 ± 1.5 mJ/m 2 . At a thickness of 40 μm, the coating has at 500 nm a transmittance of >99% measured against its glass substrate, a remarkable nanoindentation hardness H value of 1.4 GPa, and a pencil hardness of > 9H. After being abraded for 300 strokes under a pressure of 26 kPa with steel wool, the coating exhibits no noticeable degradation in its ink contraction properties. At a thickness of 10 μm on a poly(ethylene terephthalate) film, the coating can undergo inward (on the inner surface of the bend) and outward bending to radii <1 and <2 mm, respectively, without cracking. Aside from being a superb candidate as a protective antismudge coating for foldable smartphones, this marvelous material should also have many other applications.
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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 | 0.001 |
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".