Flow instabilities of PP filled with crosslinked EPDM rubber : using rheology to understand and control its occurrence
Bibliographic record
Abstract
Thermoplastic vulcanizates (TPVs) are polymer blends that have good processability like their thermoplastic phase and good elasticity like their elastomeric phase. They consist of a high amount of dynamically cured rubber particles which make flow instability such as melt fracture intense and complicated. In this study a comprehensive rheological analysis is performed to gain a deep understanding of TPVs’ flow instabilities and identify the key parameters that control them. First, a thorough linear viscoelastic analysis is performed using several groups of TPVs which are systematically different in curing level, types of polymer components, and cured rubber content. All the TPVs show a non-terminal behavior reaching to an equilibrium modulus at low frequencies/high relaxation times. The equilibrium modulus, Gy, is an indication of the existence of yield stress and the linear modulus, G(t) can be modeled by a simple power-law model in the form of (𝐺(𝑡)−𝐺𝑦)∝𝑡−𝑝, where t is the time. A yield stress is also observed in the extensional tests and the relationship between extensional and shear yield stress is investigated. Due to the presence of oil and high amount of rubber particles, TPVs show wall slip. The multimode integral Kaye-Bernstein-Kearsley-Zapas (KBKZ) constitutive model considering wall slip is applied to study and model the TPVs’ non-linear behavior. To incorporate slip into the model, a new way is used by applying a fraction of imposed nominal strain to match the experimental data. Moreover, it is assumed that the material does not slip in the linear unyielding region i.e., for shear stresses less than the yield stress. Applying these assumptions, the KBKZ captures the experimental data well. Finally, to study processing parameters that affect the melt fracture phenomenon, capillary experiments are performed. It is observed that TPVs slip massively in capillary flow. Surface fracture of the TPVs gets better with shear rate indicating that the origin of melt fracture is different with that of TPV’s pure component. Yield stress controls flow instability of the TPVs and to overcome and/or mitigate melt fracture, high shear rates are needed to cause flow and eliminate unyielded regions in the complex geometries used in real processing.
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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".