Mussel‐Inspired Molecular Strategies for Fabricating Functional Materials With Underwater Adhesion and Self‐Healing Properties
Bibliographic record
Abstract
The exceptional underwater adhesion and self-healing capabilities of mussels have fascinated researchers for over two decades. Extensive studies have shown that these remarkable properties arise from a series of reversible and dynamic molecular interactions involving mussel foot proteins. Inspired by these molecular interaction strategies, numerous functional materials exhibiting strong underwater adhesion and self-healing performance have been successfully developed. This review systematically explores the nanomechanical mechanisms of mussel-inspired molecular interactions, mainly revealed by direct force measurement techniques such as surface forces apparatus and atomic force microscopy. The development of functional materials, including coacervates, coatings, and hydrogels, with underwater adhesion and self-healing properties, is then summarized. Furthermore, the macroscopic material performances are correlated with the underlying molecular mechanisms, providing valuable insights for the rational design of next-generation mussel-inspired functional materials with enhanced underwater adhesion and self-healing properties.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".