Synthesis and properties of polystyrene‐<i>g</i>‐mSiO<sub>2</sub> filled polypropylene nanocomposites
Bibliographic record
Abstract
Abstract Hydrophobically modified nanosilica was prepared from tetraethoxysilane (TEOS) and γ‐methacryloxypropyltrimethoxysilane (MPS) by a two step sol‐gel process. The polystyrene‐grafted‐modified nanosilica (PS‐g‐mSiO2) hybrid particles were prepared by grafting polystyrene onto the resulting hydrophobically modified nanosilica by dispersion polymerization. The hybrid nanoparticles were subsequently used as the filler to fabricate polypropyrene (PP) nanocomposites. The crystallization kinetics, crystal morphology and crystallization phase component of PS‐g‐mSiO2/PP nanocomposite were studied using a differential scanning calorimeter (DSC), polarizing optical microscopy (POM) and X‐ray diffraction (XRD). Crystallization half life (t1/2) decreased, while the Arami exponent (n) of PS‐g‐mSiO2/PP nanocomposite increased compared with that of virgin PP. A rheological study allowed the unambiguous characterization of the dispersibility of nanosilicas in PS‐g‐mSiO2/PP nanocomposite. The storage modulus, melt viscosity and the elongation to break of the PS‐g‐mSiO2/PP nanocomposite were found to be strongly dependent on the grafting of PS on nanosilicas. POLYM. COMPOS., 2010. © 2009 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".