Dielectric properties of epoxy/montmorillonite nanocomposites and nanostructured epoxy/SiO<sub>2</sub>/Montmorillonite Microcomposites
Bibliographic record
Abstract
Composites reinforced with microparticles using a polymer matrix reinforced by nanoparticles represent a new emerging class of materials. Epoxy composites have been prepared using quartz as microfillers and organically modified Montmorillonite as nanofillers in order to study the dielectric properties of such new materials. The structure of the composites as determined by transmission electron microscopy, is neither exfoliated nor intercalated, although the thickness of C30B stacks is in the nanometric range. The influence of nano‐ and microparticles on epoxy matrix amorphous structure has been highlighted through Differential Scanning Calorimetry experiments. C30B has not effect on glass transition temperature but a drastic from 357 K to 325 K decrease is observed with the addition of microparticles. Heat capacity step remains unchanged, except for the microcomposite. And finally, Broadband Dielectric Spectroscopy has been used to characterize the dielectric properties at different temperatures. The spectra have been fitted with Havriliak–Negami equation to extract the relaxation times and the dielectric strengths associated with local β and γ relaxations and the main α relaxation. POLYM. COMPOS., 115–124, 2016. © 2014 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".