Healing through Histidine: Bioinspired Pathways to Self-Healing Polymers via Imidazole–Metal Coordination
Bibliographic record
Abstract
Biology offers a valuable inspiration toward the development of self-healing engineering composites and polymers. In particular, chemical level design principles extracted from proteinaceous biopolymers, especially the mussel byssus, provide inspiration for design of autonomous and intrinsic healing in synthetic polymers. The mussel byssus is an acellular tissue comprised of extremely tough protein-based fibers, produced by mussels to secure attachment on rocky surfaces. Threads exhibit self-healing response following an apparent plastic yield event, recovering initial material properties in a time-dependent fashion. Recent biochemical analysis of the structure–function relationships defining this response reveal a key role of sacrificial cross-links based on metal coordination bonds between Zn2+ ions and histidine amino acid residues. Inspired by this example, many research groups have developed self-healing polymeric materials based on histidine (imidazole)–metal chemistry. In this review, we provide a detailed overview of the current understanding of the self-healing mechanism in byssal threads, and an overview of the current state of the art in histidine- and imidazole-based synthetic polymers.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".