Synergetic effect of crystal nucleating agent and melt self-enhancement of isotactic polypropylene on its rheological and microcellular foaming properties
Bibliographic record
Abstract
Crystal nucleating agent Bis (3, 4- dimethylbenzylidene) sorbitol (DMDBS) was used to tune the melt strength and microcellular foaming properties of isotactic polypropylene (iPP) in this study. Rheological testing results reveal that the introduction of DMDBS could enhance the storage modulus and complex viscosity of iPP, obviously increase its crystallization onset temperature, compared to its counterparts without DMDBS. The addition of DMDBS could also significantly increase the cell nucleating ability of iPP, due to its large surface, cooperating with a thermal history control treatment. Quite fine microcellular iPP/DMDBS foams were fabricated with relatively small average cell sizes of nano to several micrometers, and cell densities up to 10 11 ∼10 12 cells/cm 3 , using the synergy effect of DMDBS and iPP’s melt self-enhancement. Under a comparatively low re-saturation pressure of 8 to 12 MPa, ideal microcellular foams could be generated, at a temperature zone of 158 to 162°C, which is slightly below to iPP’s original pellets nominal melting point.
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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".