Tailoring Interfacial, Rheological, and Energy Absorption Properties of In Situ Nanofibrillated Ethylene Propylene Diene Monomer Rubber for Enhanced Toughness in Polypropylene Composites
Bibliographic record
Abstract
Enhancing the mechanical performance of polymer composites is crucial for extending their service life and reducing waste. In situ fibrillation has emerged as an effective strategy for toughening rubber-modified thermoplastics. This study presents a simple yet versatile approach to further improve the toughening efficiency of in situ fibrillated rubber, focusing on polypropylene (PP) and ethylene-propylene-diene monomer (EPDM) composites. The strategy involves two steps: first, blending two EPDM grades with different viscosities in various ratios, and second, incorporating this EPDM mixture into a PP matrix, where in situ fibrillation forms nanofibrillar domains. By tuning the EPDM ratio, we control its interfacial affinity with PP, rheological behavior, and intrinsic energy absorption, producing nanofibrils ranging from ∼250 nm to <50 nm in diameter. The morphology, rheology, crystallization, and mechanical properties of the composites were investigated, revealing that an EPDM phase with equal parts of both grades achieved optimal toughening─enhancing elongation at break by ∼400% at −10 °C, ∼250% at room temperature, and impact toughness by ∼200%. This approach provides a systematic framework for optimizing in situ fibrillated rubbers, enabling more effective design of high-performance toughened thermoplastics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".