Mechanical and morphological properties of wood plastic composites based on municipal plastic waste
Bibliographic record
Abstract
Abstract Production and characterization of wood plastic composites (WPC) from the light fraction of municipal plastic wastes (post‐consumer) and wood processing residues (sawdust) were investigated. Composition analysis revealed the presence of polyethylene (PE) and polypropylene (PP) as the two main components of the matrix. In order to improve compatibility and adhesion between all the phases, an ethylene–octene copolymer was used to compatibilize the polymer phases and was also acting as an impact modifier, while the addition of maleated polyethylene and maleated polypropylene (MAPP) were acting as coupling agents between the polymer matrix and the wood flour. The combined effect of all the components was found to produce composites with interesting morphological (dispersion and adhesion) and mechanical properties (tension, torsion, flexion, and impact) after optimization of the additive package (blend of coupling agents). POLYM. COMPOS., 2013. © 2013 Society of Plastics Engineers
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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".