Graphene/montmorillonite hybrid nanocomposites based on polypropylene: Morphological, mechanical, and rheological properties
Bibliographic record
Abstract
The preparation and characterization of hybrid nanocomposites based on polypropylene (PP) with Moroccan montmorillonite (MMT)/graphene nanosheets (GNs) is reported in this article. In particular, hybrid nanocomposites were prepared by melt compounding for different MMT:GNs ratio for a total loading of 3 wt%. From the samples produced, nanofiller dispersion in the polymer was monitored by scanning electron microscopy and Fourier transform infrared spectroscopy was used to better understand the interactions between both nanofillers and the matrix. Then, tensile and torsion tests were performed to characterize the nanocomposites in the solid state, while rheological properties were obtained in the melt state to better understand the complete behavior of these hybrid nanocomposites. The results show that GNs is more effective than MMT at modifying the properties of these nanocomposites, but taking everything into account, a 50/50MMT/GNs ratio is optimum which represents a good balance between strength, ductility, and rigidity under the conditions tested. POLYM. COMPOS., 39:2046–2053, 2018. © 2016 Society of Plastics Engineers
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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".