PP-Blends with Tailored Foamability and Mechanical Properties
Bibliographic record
Abstract
The optimisation of physical foaming of branched Daploy ™ WB130HMS polypropylene foam resin and corresponding blends with a Polypropylene Blockcopolymer are described in this paper. The resulting foam morphologies of blends consisting of linear and branched polypropylene materials produced at various processing temperatures were studied using a single-screw tandem foam extrusion system and their volume expansion behaviours were compared. Three different die geometry's were tested for physical foaming of PP-blends using 5 and 10 wt% of butane. A correlation between extensional rheology and lower limit of foam density for blends was found. Depending on die geometry the use of different concentrations of branched polypropylene resin in the blends was required to achieve foam densities < 50 kg/m 3 . The influence of foam density and blend ratio on mechanical properties of foams will be discussed on a model and representative samples.
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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".