Extensional rheology of PP/PS/MWCNT electrically conductive polymer composites
Bibliographic record
Abstract
Polymer blends with co-continuous morphologies have gained significant attention due to their potential as electrically conductive materials when filled with conductive fillers, such as carbonaceous nanoparticles. These advanced materials are widely used in applications such as electronics, sensors, energy storage devices, and electromagnetic (EM) shielding. The co-continuous structure of these blends enables efficient distribution of conductive fillers, achieving what is known as double percolation. In this state, the filler is primarily located within one polymer phase or at the interface between phases, significantly reducing the percolation threshold - the critical concentration needed for the material to exhibit electrical conductivity. This not only improves performance but also reduces production costs by minimizing filler usage. Despite these advantages, the electrical properties of such composites can be significantly affected during processing and post-processing. Deformations encountered in manufacturing processes like film extrusion, blow molding, and other techniques can disrupt the conductive network, leading to a deterioration or the complete disappearance of electrical conductivity. Therefore, understanding how extensional and shear flows impact the electrical performance and morphology of these composites is crucial for optimizing their functionality in end-use applications such as EM shielding and electronics packaging. In this study, the extensional rheology of polypropylene/polystyrene blends filled with multiwall carbon nanotubes (PP/PS/MWCNT) was systematically investigated. Composites with varying MWCNT concentrations (0-5 wt.%) were prepared using conventional melt mixing. Transient stress growth experiments were conducted at various Hencky strain rates using a universal extensional fixture (UXF) on an Anton Paar MCR 702e TwinDrive rheometer. Extensional results were compared to shear rheology findings to examine differences in electrical properties. The evolution of electrical conductivity during applied shear deformation was monitored using a rheometer coupled with an impedance meter, while changes in conductivity following extensional deformation were evaluated with the 4-probe method.
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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".