Poly(methyl methacrylate)/Graphene Oxide Nanocomposites by a Precipitation Polymerization Process and Their Dielectric and Rheological Characterization
Bibliographic record
Abstract
We report a method for achieving controlled dispersion of graphene oxide (GO) in poly(methyl methacrylate) (PMMA) via the precipitation polymerization process in a water/methanol mixture. GO acts as a surfactant and adsorbs on the interface between polymerized PMMA particles and solvent mixture. Scanning electron and transmission electron microscopy confirmed that the precipitate consists of polymer particles (<1 μm) surrounded by the GO sheets. Compression molding of the precipitate yields a polymer nanocomposite with the GO organized into a regularly spaced 3D network which percolates at 0.2 wt % GO. Simple thermal reduction of the GO sheets dispersed in PMMA at relatively low temperature (210 °C) achieved electrical conductivity higher than 10 –2 S/m at 0.4 wt % of GO. Parallel dielectric and rheological characterization demonstrated that the thermal reduction is a quite fast process without significant degradation of the polymer. The study should open up new opportunities in the design of GO-based polymer nanocomposites.
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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 | 0.000 | 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) | 0.000 | 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".