Viscosity and interfacial properties in a mussel-inspired adhesive coacervate
Bibliographic record
Abstract
The chemistry of mussel adhesion has commanded the focus of much recent research activity on wet adhesion. By comparison, the equally critical adhesive processing by marine organisms has been little examined. Using a mussel-inspired coacervate formed by mixing a recombinant mussel adhesive protein (fp-151-RGD) with hyaluronic acid (HA), we have examined the nanostructure, viscosity, friction, and interfacial energy of fluid-fluid phase-separated coacervates using the surface forces apparatus and microscopic techniques. At mixing ratios of fp-151-RGD:HA resulting in marginal coacervation, the coacervates showed shear-thickening viscosity and no structure by cryo-transmission electron microscopy (cryo-TEM). However, at the mixing ratio producing maximum coacervation, the coacervate showed shear-thinning viscosity and a transition to a bicontinuous phase by cryo-TEM. The shear-thinning viscosity, high friction coefficient (>1.2), and low interfacial energy (<1 mJ m(-2)) observed at the optimal mixing ratio for coacervation are promising delivery, spreading and adhesion properties for future wet adhesive and coating technologies.
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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 | 0.001 |
| 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 | 0.001 |
| 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 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".