Catalyst-Free Synthesis of Betulin-Based Polyurethane Elastomers with Outstanding Mechanical Properties and Solvent Resistance
Bibliographic record
Abstract
Using sustainable biomass feedstock to prepare biobased chemical products is attracting increasing attention. Betulin is a natural cyclic aliphatic diol that can be extracted in large quantities from the bark of birch trees. In this study, a series of bio-based polyurethane (PU) elastomers with excellent mechanical properties, solvent resistance, and thermal stability were synthesized under catalyst-free conditions using betulin and castor oil (CO) as the bio-based polyols. The chemical structure and properties of the bio-based PU elastomers were systematically investigated according to the effect of the hydroxyl ratio between betulin and CO. Due to the presence of abundant hydrogen bonds and rigid ring planes in the PU structure, and a higher cross-link density, the obtained PU elastomers had excellent mechanical properties. They achieved a maximum tensile strength of 31.6 MPa with the tensile strain reaching more than 200% and were able to withstand 1 × 10 5 times their weight. The thermal decomposition temperature of the betulin-derived PUs was over 300 °C. This study showcased a strategy to synthesize sustainable high-performance PU materials with a high biomass content (>75%).
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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) | 0.000 | 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 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".