Tough and Self-Healing Recycled Polyurethanes with Tunable Fluorescence by Chain Aggregation
Bibliographic record
Abstract
Recycling of thermoset polyurethanes (PUs) has aroused wide-ranging concerns. However, degraded thermoset PUs face great challenges in effectively rebuilding the network for multifunctional upgradation due to random chain breakage. Herein, we incorporate anionically polymerized poly(maleimide) (PM) into the reconfigured PU network to achieve improved mechanical and self-healing properties, and tunable emission of the recycled PU by chain aggregation. The aggregation of PM or degraded PU fragments via hydrogen bonding interactions forms three main cluster luminophores, of which the changing relative proportion gives rise to tunable emission (from blue to green). Meanwhile, hydrogen bonding interactions between the PM and PU chains serve as sacrificial bonds and dynamic bonds to enhance the mechanical properties (61.7 MJ/m 3, increased by 52 times) and self-healing abilities (86.6%), respectively. The design of chain aggregation opens up a new perspective for the multifunctional upgradation of recycled PU and greatly facilitates the value-added utilization of waste thermoset PUs.
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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) | 0.000 | 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 | 0.000 |
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 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".