Sequential Interpenetrating Polymer Networks Produced from Vegetable Oil Based Polyurethane and Poly(methyl methacrylate)
Bibliographic record
Abstract
Sequential interpenetrating polymer networks (IPNs) were prepared using polyurethane produced from a canola oil based polyol with primary terminal functional groups and poly(methyl methacrylate) (PMMA). The properties of the material were studied and compared to the IPNs made from commercial castor oil using dynamic mechanical analysis, differential scanning calorimetry, as well as tensile measurements. The morphology of the IPNs was investigated using scanning electron microscopy and transmission electron microscopy. The chemical diversity of the starting materials allowed the evaluation of the effects of dangling chains and graftings on the properties of the IPNs. The polymerization process of canola oil based IPNs was accelerated because of the utilization of polyol with primary functional groups, which efficiently lessened the effect of dangling chains and yielded a higher degree of phase mixing. The mechanical properties of canola oil based IPNs containing more than 75 wt % PMMA were comparable to the corresponding castor oil based IPNs; both were superior to those of the constituent polymers due to the finely divided rubber and plastic combination structures in these IPNs. However, when PMMA content was less than 65 wt %, canola oil based IPNs exhibited a typical mechanical behavior of rigid plastics, whereas castor oil based IPNs showed a typical mechanical behavior of soft rubber. It is proposed that these new IPN materials with high performance prepared from alternative renewable resources can prove to be valuable substitutes for existing materials in various applications.
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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 | 0.000 | 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".