High‐Performance, Light‐Stimulation Healable, and Closed‐Loop Recyclable Lignin‐Based Covalent Adaptable Networks
Bibliographic record
Abstract
Abstract In this work, high‐performance, light‐stimulation healable, and closed‐loop recyclable covalent adaptable networks are successfully synthesized from natural lignin‐based polyurethane (LPU) Zn 2+ coordination structures (LPUxZy). Using an optimized LPU (LPU‐20 with a tensile strength of 28.4 ± 3.5 MPa) as the matrix for Zn 2+ coordination, LPUs with covalent adaptable coordination networks are obtained that have different amounts of Zn. When the feed amount of ZnCl 2 is 9 wt%, the strength of LPU‐20Z9 reaches 37.3 ± 3.1 MPa with a toughness of 175.4 ± 4.6 MJ m −3 , which is 1.7 times of that of LPU‐20. In addition, Zn 2+ has a crucial catalytic effect on “dissociation mechanism” in the exchange reaction of LPU. Moreover, the Zn 2+ ‐based coordination bonds significantly enhance the photothermal conversion capability of lignin. The maximum surface temperature of LPU‐20Z9 reaches 118 °C under the near‐infrared illumination of 0.8 W m −2 . This allows the LPU‐20Z9 to self‐heal within 10 min. Due to the catalytic effect of Zn 2+ , LPU‐20Z9 can be degraded and recovered in ethanol completely. Through the investigation of the mechanisms for exchange reaction and the design of the closed‐loop recycling method, this work is expected to provide insight into the development of novel LPUs with high‐performance, light‐stimulated heal ability, and closed‐loop recyclability; which can be applied toward the expanded development of intelligent elastomers.
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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 | 0.001 | 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) | 0.000 | 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".