Supramolecular Peptide Gels: Influencing Properties by Metal Ion Coordination and Their Wide-Ranging Applications
Bibliographic record
Abstract
Supramolecular gels have been an area of interest in many research fields. They provide a means to understand assembly of nanostructures, and through the use of amino acid- and peptide-based gelators they can give insights into the similar assembly pathways of their more complex structural counterparts. Bio-inspired metal coordination, such as histidine-copper coordination, in the supramolecular assembly of these gelators is one method for furthering our understanding and development of these materials. Metal-gelator coordination mimics biologically relevant metal-peptide coordination, thus influencing hydrogel self-assembly and mechanical properties, including biodegradability, biocompatibility, tunability, and recyclablity, while the metal coordination can functionalize the gels to allow for widespread applications in biomedical industries (e.g., drug delivery), waste management, and catalysis. This review aims to discuss recent insights into the supramolecular assembly of gels involving metal ions, as well as a few key areas of application using metal interactions and incorporation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".