Porous Non‐Isocyanate Polyurethane by Stepwise Polymerization‐Induced Micron Phase Separation between Evolving Polymer Network and Solvent
Bibliographic record
Abstract
Abstract Porous polyurethane accounts for half the global polymer foam market. However, the synthesis of polyurethanes (PUs) heavily relies on the use of highly toxic isocyanates, raising significant health and environmental concerns. Non‐isocyanate polyurethane (NIPU), as a safer alternative, has emerged via the polymerization of multifunctional cyclic carbonates and amines. Nevertheless, NIPUs are seldom explored as porous materials compared to conventional PUs primarily because their synthesis is based on isocyanate‐free cyclic carbonate‐amine chemistry, making it challenging to replicate the foaming process of traditional PUs, which relies on in situ CO 2 production through isocyanate hydrolysis. In this study, the highly efficient preparation of porous NIPU through step‐growth polymerization‐induced micron phase separation between the evolving polymer network and the solvent is reported. A series of NIPUs with unconventional porous structures are facilely prepared via a convenient one‐pot method in the absence of catalysts and any in situ generated or additional blowing agents at room temperature and atmospheric pressure. Furthermore, this strategy can be successfully extended to the production of flexible NIPU/cellulose fabric hybrid porous materials. This strategy provides a facile approach to accessing porous NIPU and NIPU hybrid materials, which is beneficial to the wide applications of NIPUs in different fields.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".