Sustainable Biocomposites from Pyrolyzed Grass and Toughened Polypropylene: Structure–Property Relationships
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A novel class of injection-molded, toughened biocomposites was engineered from pyrolyzed miscanthus-based biocarbon, poly(octene ethylene) elastomer, and polypropylene (PP). The elastomer and biocarbon were added to the PP matrix at 30 and 20 wt %, respectively. The particle size of the biocarbon varied within two main ranges: <20 and 106-125 μm. The morphology and adhesion between the filler and the matrix were controlled by the addition of maleic anhydride grafted PP (MAPP). The composites were melt-blended and then injection-molded to tensile, flexural, and impact bars. The results showed that although the morphology of the composite is almost independent of particle size it is greatly dependent on the addition of MAPP. Two completely different morphologies, separate dispersion and encapsulated filler particles, were obtained in the presence and absence of MAPP, which was verified by atomic force and scanning electron microscopies. Model calculations based on a modified Kerner equation showed that the encapsulated filler content decreased from 64 to 8% by the addition of MAPP, which caused a major improvement in the stiffness and strength of the composites. Despite having a different morphology caused by the compatibilizer, composites with smaller particles exhibited better strength and modulus and lower impact toughness compared to those with a larger particle size. Results suggest that the failure mechanisms are mainly controlled by the local fracturing of biocarbon particles, which was more pronounced when the particle size was larger.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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