Catalyst-Free Biodegradable Chitosan-Based Dual Dynamic Covalent Networks with Self-Healing and Flame-Retardant Properties
Bibliographic record
Abstract
Synthesizing covalent adaptable networks (CANs) from chitosan has been difficult due to its inherent insolubility in organic solvents. In this study, we report a facile approach for obtaining biobased flame-retarding CANs using chitosan as the starting material without dissolving it. These novel CANs were prepared via a dual cross-linking strategy in which chitosan consecutively reacted with citric acid and a vanillin-based cross-linker containing a flame-retarding moiety. The chitosan-based CANs attained dual dynamic bond-exchange sites resulting from generation of amide and ester linkages, which enabled them to perform self-healing and recyclability. They also possessed remarkable flame-retarding performance (e.g., limiting oxygen index of 41.5% and UL-94 V-0 rating), surpassing other chitosan-based flame retardants reported in the literature to date. By investigating the CAN’s response to fire in both gas and condensed phases, their flame-retarding mechanisms were uncovered. This study pinpoints a promising approach to make biobased, biodegradable, and multifunctional CANs from chitosan.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".