The influence of matrix viscosity and composition on the morphology, rheology, and mechanical properties of thermoplastic elastomer nanocomposites based on EPDM/PP
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Bibliographic record
Abstract
Abstract The morphological and rheological properties of thermoplastic elastomer nanocomposites (TPE nanocomposites) were studied using different viscosities of polypropylene (PP) and ethylene‐propylene‐diene monomer (EPDM) rubber content (20, 40, 60 wt%). The components, namely EPDM, PP, Cloisite 15A, and maleic anhydride‐modified PP as compatibilizer, were compounded by a one‐step melt mixing process in a laboratory internal mixer. The structure of the nanocomposites was characterized with X‐ray diffraction, scanning electron microscopy, transmission electron microscopy, and rheometry in small amplitude oscillatory shear. The distribution state of the clay between the two phases (PP and EPDM) was found to be dependent on the viscosity ratio of PP to EPDM. In the nanocomposites prepared based on low viscosity PP (LVP) and EPDM, the clay was mostly dispersed into the PP phase and the size of the dispersed rubber particles decreased in comparison with unfilled but otherwise similar blends. However, the dispersed elastomer droplet size in the high viscosity PP (HVP) blends containing 40 and 60% EPDM increased with the introduction of the clay. For TPE nanocomposites, the dependence of the storage modulus ( G ′) on angular frequency (ω) followed a clear nonterminal behavior. The increase in the storage modulus and the decrease in the terminal zone slope of the elastic modulus curve were found to be larger in the LVP nanocomposite in comparison with the HVP sample. The yield stress of nanoclay‐filled blends prepared with LVP increased more than that of HVP samples. The tensile modulus improved for all nanocomposites but a higher percentage of increase was observed in the case of LVP samples. POLYM. COMPOS., 2008. © 2008 Society of Plastics Engineers
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| 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 it