<i>In Situ</i> Visualization of Extensional Flow-Induced Crystallization in Polypropylene under High-Pressure CO<sub>2</sub>
Bibliographic record
Abstract
The crystallization behavior of semicrystalline polymers under foaming-relevant conditions is among the most critical factors dictating the morphology and properties of any foam product. While cell nucleation and growth are often discussed in the plastics foaming literature, extensional flow-induced crystallization experienced postdie exit during foam stabilization is overlooked. To address this gap, we aim to build a comprehensive understanding of the nonisothermal crystallization behavior under the effects of CO 2 pressure, uniaxial extensional flow, and long-chain branching. Two grades of polypropylene (PP) were used: one linear and one long-chain branched. Under quiescent conditions, an increase in CO 2 pressure led to a decrease in onset crystallization temperatures, a decrease in crystal growth rates, and an increase in nucleation densities in both resins. Additionally, X-ray diffraction analyses showed the promotion of γ-crystals under higher CO 2 pressures. Upon the introduction of uniaxial extensional flow, both resins nucleated elongated crystals (i.e., cylindrites) due to chain alignment and stretching. These cylindrites were observed via atomic force microscopy and shown to exhibit the classical shish–kebab structure. Interestingly, the long-chain-branched PP (LCB PP) nucleated more cylindrites with higher aspect ratios and exhibited a crystallization rate faster than that of its linear counterpart. Rheological characterization showed that this difference emerged from the longer relaxation behavior of the LCB PP chains. These findings may present value in modeling polymer processes while emphasizing the role of extensional flow-induced crystallization during cell growth and stabilization.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".