Metal–Ligand Interactions and Salt Bridges as Sacrificial Bonds in Mussel Byssus-Derived Materials
Bibliographic record
Abstract
The byssus that anchors mussels to solid surfaces is a protein-based material combining strength and toughness as well as a self-healing ability. These exceptional mechanical properties are explained in part by the presence of metal ions forming sacrificial bonds with amino acids. In this study, we show that the properties of hydrogel films prepared from a byssus protein hydrolyzate (BPH) can also be improved following the biomimetic formation of sacrificial bonds. Strengthening and toughening of the materials are both observed when treating films with multivalent ions (Ca 2+ or Fe 3+ ) or at the BPH isoelectric point (pI) as a result of the formation of metal–ligand bonds and salt bridges, respectively. These treatments also provide a self-healing behavior to the films during recovery time following a deformation. While pI and Ca 2+ treatments have a similar but limited pH-dependent effect, the modulus, strength, and toughness of the films increase largely with Fe 3+ concentration and reach much higher values. The affinity of Fe 3+ with multiple amino acid ligands, as shown by vibrational spectroscopy, and the more covalent nature of this interaction can explain these observations. Thus, a judicious choice of treatments on polyampholyte protein-based materials enables control of their mechanical performance and self-healing behavior through the strategic exploitation of reversible sacrificial bonds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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) | 0.001 | 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 teacher head, 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".