Degradation Behavior of Polypropylene during Reprocessing and Its Biocomposites: Thermal and Oxidative Degradation Kinetics
Why this work is in the frame
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Bibliographic record
Abstract
Non-isothermal thermogravimetric analysis (TGA) was employed to investigate the degradation of polypropylene (PP) during simulated product manufacturing in a secondary process and wood–plastic composites. Multiple batch mixing cycles were carried out to mimic the actual recycling. Kissinger–Akahira–Sunose (KAS), Ozawa–Flynn–Wall (OFW), Friedman, Kissinger and Augis models were employed to calculate the apparent activation energy (Ea). Experimental investigation using TGA indicated that the thermograms of PP recyclates shifted to lower temperatures, revealing the presence of an accelerated degradation process induced by the formation of radicals during chain scission. Reprocessing for five cycles led to roughly a 35% reduction in ultimate mixing torque, and a more than 400% increase in the melt flow rate of PP. Ea increased with the extent of degradation (α), and the dependency intensified with the reprocessing cycles. In biocomposites, despite the detectable degradation steps of wood and PP in thermal degradation, a partial coincidence of degradation was observed under air. Deconvolution was employed to separate the overlapped cellulose and PP peaks. Under nitrogen, OFW estimations for the deconvoluted PP exposed an upward shift of Ea at the whole range of α due to the high thermal absorbance of the wood chars. Under air, the Ea of deconvoluted PP showed an irregular rise in the initial steps, which could be related to the high volume of evolved volatiles from the wood reducing the oxygen diffusion.
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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 it