Catalyst‐Free Synthesis of Covalent Adaptable Network (CAN) Polyurethanes from Lignin with Editable Shape Memory Properties
Bibliographic record
Abstract
Abstract Here a new strategy of catalyst‐free direct synthesis of covalent adaptable network polyurethanes (LPUs) from lignin with editable shape memory effect is reported. Using unmodified lignin, PEG, and isocyanate under the condition of the isocyanate index less than 1.0 (NCO/OH<1.0), a variety of LPUs are obtained. When NCO/OH=0.8, a stable cross‐linked network can be formed (ex. the gel content of LPU50‐0.8 was 98±0.3 %). The activation energy ( E a ) value of LPUs is similar to that of polyhydroxyurethanes (PHUs), at around 110 kJ mol −1 . With an increase of lignin content, the LPUs show a transition from ductile fracture to brittle fracture mode. And the mechanical properties of LPUs are significantly enhanced after extrusion processing, with the maximum modulus reaching 649±26 MPa and the maximum toughness up to 9927±111 kJ m −3 . The improvement in mechanical properties is due to the homogenization of complex cross‐linked network under the powerful external force of the extruder and the lignin that originally was free in the system participated in the exchange reactions. Moreover, LPUs can also be prepared continuously in one step by using an extruder as the reactor. In addition, LPU50‐0.8 has an editable shape memory effect. This study develops a novel method for the synthesis of LPU from lignin with NCO/OH<1.0, showcasing new possibilities for value‐added utilization of lignin, and expands the bio‐based products portfolio from biomass feedstock to help meet future green manufacturing demands.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".