Dielectric spectroscopy of poly(ethylene oxide)–carbon nanotube nanocomposites
Bibliographic record
Abstract
The dielectric properties of poly(ethylene oxide)–multiwalled carbon nanotube (MWCNT) nanocomposites have been studied over a wide range of frequency (0.1–106 Hz) and temperature (180–300 K). Nanocomposites were prepared by both melt mixing and twin-screw extrusion, and the concentration of MWCNTs was varied from 0 to 5 wt. %. Both the real and imaginary parts of the complex permittivity increase with the increasing MWCNT concentration. We observe a percolation transition in the DC conductivity of the composites above a critical MWCNT concentration pc. The data from the twin-screw extruded samples give a very well-defined value of pc and a percolation exponent of 1.9 ± 0.2, in good agreement with theoretical predictions. In contrast, both the percolation threshold and the critical exponent were more poorly defined for the melt-mixed nanocomposites. This indicates that the conductive properties of these materials can strongly depend on the details of sample preparation. Our data suggest that the dc conductivity of the nanocomposites is due to the conduction along the nanotubes, coupled with thermally activated transport of electrons across thin polymer bridges, which separate the nanotubes. The frequency dependence of the dielectric spectrum was studied as a function of temperature and composition. The primary dielectric relaxation process is due to the motions of electric dipoles on the polymer backbone. At low MWCNT concentrations, the relaxation involves the entire polymer chains and is slowed substantially when a low concentration of MWCNT is added. At higher MWCNT concentrations, the relaxation becomes much faster. We attribute this to binding of the polymer chains to the nanotubes, which reduces the length of the chain segments contributing to the dielectric relaxation.
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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".