Oil-Infused Silicone Prevents Zebra Mussel Adhesion
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Bibliographic record
Abstract
(zebra mussel) causes extensive damage each year. The adhesive interface between the substrate surface and the mussels' adhesive plaques plays a key role in zebra mussel biofouling. Silicone-oil-infused polydimethylsiloxane (iPDMS), an omniphobic material in the class of liquid-infused slippery surfaces, has been shown to develop a uniform, microscale, antifouling surface oil layer, which we hypothesized would be effective against zebra mussel fouling. iPDMS substrates with varying levels of oil saturation were tested for their ability to disrupt mussel adhesion by characterizing zebra mussel reattachment in a simulated freshwater environment for 3 days. On fully saturated iPDMS samples or those near full saturation, zebra mussels showed no reattachment, compared to 41% reattachment on PDMS controls (no oil infusion). For lower saturation levels, the frequency of reattachment was decreased relative to PDMS controls. Mussel detachment forces decreased in iPDMS as compared to PDMS, and adhesive failures occurred more frequently with higher iPDMS saturations. Surface analysis of the subsaturated iPDMS substrates showed incomplete coverage of the surface oil layer. After 3 days of immersion in artificial freshwater, subsaturated iPDMS substrates showed a decrease in slipperiness (measured by water slide angle), whereas in fully saturated iPDMS, the slipperiness was unchanged, despite no observed oil loss in either group. The decrease in slipperiness is attributed to microfouling of the subsaturated substrates, consistent with incomplete surface oil layer coverage, and supports the notion that full oil layer coverage is required for effective antifouling properties. Employing iPDMS as an antifouling coating shows promise against freshwater mussel adhesion, and this work further aids in understanding the antifouling mechanism of iPDMS and the role of the plaque-substrate interface in freshwater mussel adhesion.
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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 | 0.000 | 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) | 0.002 | 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 it