Sustainable Composites from Biodegradable Polyester Modified with Camelina Meal: Synergistic Effects of Multicomponents on Ductility Enhancement
Bibliographic record
Abstract
Biodegradable composites were prepared via a melt compression molding process with dehulled camelina meal (DeCM) as the biomass-based filler and poly(3-hydroxybutyrate- co -4-hydroxybutyrate) (P(3,4)HB) or poly(butylene succinate) (PBS) as the aliphatic polyester matrix. The incorporation of 25 parts DeCM into the composite promoted an impressive increase of 461% in the elongation at break of the P(3,4)HB-based composites. Concurrently, the elongation at break of PBS-based composites containing 20 parts of DeCM increased by 71% over the neat materials. Extraction of components from the DeCM (oil and protein) showed that oil had a critical plasticization effect that enhanced the ductility of the composites. Compared with neat materials, the presence of DeCM filler had no significant effect on the thermal properties of the composites and preserved the original crystalline structure of the polyester component in the composites. Renewable, economical, and biodegradable DeCM is a promising functional biomass-based filler for polyester-based composites, and it is worth noting that the synergistic effects of multicomponents in DeCM played a key role in ductility enhancement.
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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) | 0.001 | 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) | 0.001 | 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".