Triticale straw and its thermoplastic biocomposites
Bibliographic record
Abstract
Abstract The potential of triticale straw for the production of green composites based on polypropylene (PP) was evaluated. The composites were prepared by melt compounding of PP and chopped triticale straw (so-called triticale particles) using different formulations and triticale concentrations. The morphology and crystallization of the PP triticale composites were characterized by means of various techniques, including optical microscopy (OM), scanning electron microscopy (SEM), and differential scanning calorimetry (DSC). The composite mechanical performance was also evaluated. The results obtained demonstrate that, by simply adding triticale particles into PP, they play the role of a conventional filler that increases the modulus while reduces the strength. However, the developed formulation with the combination of coupling agent and reactive additive provides superior strength and modulus for the composites; thus, it can upgrade the triticale particles from filler to reinforcement category.
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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) | 0.000 | 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) | 0.001 | 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".