Energy‐Dissipating Polymeric Silicone Surfactants
Bibliographic record
Abstract
Materials that are able to withstand impact loadings by dissipating energy are crucial for a broad range of different applications, including personal protective applications. Shear-thickening fluids (STFs) are often used for this purpose, but their preparation is still limited, in part, to high production costs. It is demonstrated that polymeric surfactants comprised of linear telechelic sugar-modified silicones-with neither additives nor particles-generate transient polymer networks (TPNs) that represent a promising alternative to STFs. The reported polymers have distinct viscoelastic properties and can turn from a liquid into a rubbery network when force is applied. Saccharide-modified silicones with short chains (degree of polymerization (DP) ≈ 34, 68) are solids, but become energy-absorbing viscoelastic fluids when diluted in low-viscosity silicone oils; longer silicones (DP ≈ 338, 675) with low saccharide contents are viscoelastic fluids at room temperature. Excellent damping properties are found for the reported silicone surfactants, even those containing only 0.1% saccharides. The degree of energy absorption can be tailored simply by controlling the sugar/silicone ratio.
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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".