Effect of Peroxide Compounds on Biodegradable Blends Based on Poly(butylene adipate-<i>co</i>-terephthalate)/Plasticized Cellulose Acetate
Bibliographic record
Abstract
Plasticized cellulose acetate (pCA) using biobased triacetin (TA) as a plasticizer and poly(butylene adipate- co -terephthalate) (PBAT) were blended at three weight fractions (ranging from 25/75 to 75/25), using two organic peroxides, 2,5-dimethyl-2,5-di( tert -butylperoxy)hexane (Lup) and dicumyl peroxide (DCP), as compatibilizing agents. The compatibilizers, peroxide compounds, should work to achieve the miscibility of both polymers, resulting in a material with an appropriate stiffness–toughness balance for single-use and sustainable packaging applications. Scanning electron microscopy (SEM) images showed that PBAT/pCA blend ratios were completely immiscible within the range of ratios studied in this work, despite the solubility parameters indicating partial miscibility between them. Rheological properties and differential scanning calorimetry showed changes in the analyzed blends, influenced by the type (Lup or DCP), quantity (0.025–0.05 phr) of peroxide compounds, and PBAT/pCA blend ratio. DCP exhibited better compatibilization, affecting the 25/75 and 75/25 blends more than the 50/50 blends. The rheological properties of the modified 25/75 and 75/25 blends exhibited an increase of storage modulus and complex viscosity in comparison with the unmodified blends and pCA samples, confirming the cross-linking structures. The Young’s modulus and tensile strength increased by around 18 and 30%, respectively, for the modified 75/25 blend with DCP, with respect to the unmodified 75/25 sample. The introduction of free radicals to generate the PBAT- g -CA copolymer was shown to be complex. The type and amount of peroxide, the nature of polymers, and the blend ratio remarkably influenced various types of reactions, mostly interlinking and cross-linking.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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; both teacher heads agree on what is shown here.
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".