Superhydrophobic bulk ternary and quaternary silicone rubber nanocomposites: An Insight into material selection and performance evaluation
Bibliographic record
Abstract
We developed free-standing superhydrophobic bulk materials without the need for additional surface treatments, demonstrating their potential for commercial applications. The non-wetting properties of the nanocomposites were influenced by various factors, particularly the type, size, and concentration of the embedded particles. A synergic combination of surface roughness and the low surface energy of silicone rubber imparted superhydrophobicy throughout the entire material. To verify consistent bulk water repellency across the bulk, regardless of the incorporated particles, the water contact angle (CA) and contact angle hysteresis (CAH) were measured on both the surface and cross-section of the nanocomposites. To assess suitability for electrical insulation application, thermal properties were evaluated using TGA, while electrical performance was characterized through measurement of dielectric permittivity (Ɛˊ), dielectric loss (tan δ), and dry flashover voltage. Icephobicity was examined by measuring both the delay time for the onset of water droplet freezing on the surface and the force required to dislodge a column of ice from the surface. Mechanochemical durability of the produced materials were studied by various means to ensure the long-term performance of the nanocomposites. Finally, to support efficient material selection, radar diagrams were employed to compare the performance of each developed nanocomposite across all evaluation criteria.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".