Effect of filler dispersion on polypropylene morphology
Bibliographic record
Abstract
Abstract The evaluation of filler dispersion in compounding machines is an important part of their design. Calcium carbonate–filled polypropylene (PP) was used as a model compound to study filler dispersion. The evolution of dispersion was followed in a twin‐screw extruder where several types of mixing sections were evaluated. Reverse kneading blocks were found to be very efficient for breakup of agglomerates. Depending on extrusion conditions, agglomeration was observed even after the matrix was melted. To study dispersion in a single‐screw extruder, Maddock and reverse Maddock mixing elements were tried. A quantitative evaluation of the dispersion state allowed a better understanding of nucleation in the PP/CaCO 3 matrix. A significant content of the β‐phase of polypropylene was observed when the agglomerate size was relatively small. The level of shear stress was also important for the formation of the β‐phase of PP. The quantification of dispersion was mainly evaluated from micrographs of samples obtained by reflected light microscopy in conjunction with image analysis. The characterization of β‐spherulites was carried out using polarized light microscopy and scanning electron microscopy. Polym. Eng. Sci. 44:880–890, 2004. © 2004 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".