Effects of polymer molecular weight and filler particle size on flow behavior of wood polymer composites
Bibliographic record
Abstract
Abstract The influence of polymer matrix molecular weight and filler particle size on rheological properties and extrudate distortions of metallocene polyethylene (mPE)/wood flour (WF) composites has been investigated by rotational and capillary rheometers. It was found that at low shear rates smaller filler particles provide higher shear viscosity than the larger sized filler. At high shear rates and WF loadings above 30 wt%, the effect of particle size on the melt flow properties becomes negligible. The relative increase of the storage modulus with decreasing particle size is more pronounced in the case of low molecular weight polymer matrix than that in higher molecular weight polyethylene based composites. The wood filled polyethylenes exhibit extrudate surface defects, which are complex function of the shear rate, polymer matrix molecular weight, and filler particle size. Increasing the shear rate results in pressure oscillations and spurt‐flow. It was also observed that the evolution of the extrudate surface tearing is strongly dependent on the pressure during a single pressure oscillation cycle in the spurt flow regime. POLYM. COMPOS., 2008. © 2008 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 | 0.001 |
| 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".