Key Factor of Graphene Localization on Electrical Conductive Properties of Graphene Filled Polyethylene/Polypropylene Composites during Melt Blending
Bibliographic record
Abstract
The effect of surfactant-exfoliated graphene (SEG) on the morphology of SEG-filled polyethylene (PE)/ polypropylene (PP) blends has been investigated by image analysis of transmission electron microscope. The electrical conductivity of SEG-filled PE/PP composites strongly depends on the localization of SEG. From theoretical considerations of a previous paper by one of the authors, it is found that the transfer dynamics as well as the stability of different solid nano-fillers at the blends interface reveals a strong dependence on the nano-filler’s aspect ratio. The appropriate control of processing conditions and the selective localization of SEG in the PE/PP composites are key tools to design conducting polymer composites. When the selective localization of SEG is optimized at the PE/PP blends interface, the electrical conductivity reaches 1.86 × 10-5 S/m for a low percolation at 1 wt %, in sharp compared to 7 wt % if the localization of SEG has not been optimized.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".