Under-water superoleophobic Glass: Unexplored role of the surfactant-rich solvent
Bibliographic record
Abstract
Preparing low energy liquid-repellant surfaces (superhydrophobic or superoleophobic) have attracted tremendous attention of late. In all these studies, the necessary liquid repellency is achieved by irreversible micro-nano texturing of the surfaces. Here we show for the first time that a glass surface, placed under water, can be made superoleophobic (with unprecedented contact angles close to 180 degrees and roll off angles only a few fractions of 1 degree) by merely changing the surfactant content of the water medium in which the oil (immiscible in water) has been dispersed. Therefore, we propose a paradigm shift in efforts to achieve liquid-repellant systems, namely, altering the solvent characteristics instead of engineering the surfaces. The effect occurs for a surfactant concentration much larger than the critical micelle concentration, and is associated to strong adsorption of surfactant molecules at the solid surface, triggering an extremely stable Cassie-Baxter like conformation of the oil droplets.
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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".