Improvement of toughness properties of polypropylene filled with nanobentonite using stearic acid as interface modifier
Bibliographic record
Abstract
The mechanical properties of polypropylene-bentonite nanocomposites were studied in this work. In this study, stearic acid was used as both a new surface modifier of the nano bentonite and a new interface modifier during the compounding of the nanocomposites with a twin-screw extruder. Three different weight concentrations (1.5 wt.%, 2.5 wt.%, and 5.0 wt.%.) were chosen for each type of nanobentonite compounds. Fourier transform infrared spectroscopy allowed us the possibility to discard any chemical interaction between the nanobentonite and stearic acid. Nevertheless, the physical interactions between both components favored the mechanical properties, resulting in around 150% improvement in the elongation of the nanocomposites containing stearic acid as surface and interface modifier. This can be due to the good intercalation of the nanobentonite platelets as found by wide angle X-ray diffraction and this was further confirmed by scanning electron microscopy, where the fracture surface analyses of these nanocomposites showed the best dispersion and wetting of the nanoplatelets by the polymer matrix. Crystallization behavior was also modified by stearic acid incorporation and the nanocomposites with better dispersion exhibited crystallization temperatures similar to pure polypropylene.
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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 | 0.001 | 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 | 0.001 |
| 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".