X‐band dielectric properties of hybrid nanocomposites of nitrogen‐doped carbon nanotube/functionalized nanoclay/polyvinylidene fluoride nanocomposite
Bibliographic record
Abstract
Abstract This study investigates the effect of functionalized nanoclay on dielectric properties in the X‐band (8.2‐12.4 GHz) of synthesized nitrogen‐doped carbon nanotube (N‐CNT)/nanoclay/polyvinylidene fluoride (PVDF) nanocomposites prepared via melt‐mixing. Montmorillonite nanoclay was functionalized by an aminosilane coupling agent, making the nanoclay more compatible with the organic polymer. N‐CNT was synthesized employing a chemical vapor deposition technique. Transmission electron microscopy and optical microscopy were used to assess the morphology of nanocomposites. The incorporation of nanoclay improved the dielectric properties, that is, dissipation factor of N‐CNT/PVDF nanocomposites. For instance, incorporation of 0.5 wt% nanoclay into N‐CNT/PVDF nanocomposite at 1.0 wt% N‐CNT loading resulted in 61% reduction in the dissipation factor (from 0.18 ± 0.01 to 0.07 ± 0.01). The percolation threshold increased from 0.3 to 1.0 wt% of N‐CNT by incorporation of 0.5 wt% nanoclay, which expanded the percolation region. In addition, incorporation of 0.5 wt% nanoclay reduced agglomeration area ratio of 1.0 wt% N‐CNT/PVDF nanocomposite by 57%. Rheological results indicated collapse of N‐CNT networks upon addition of nanoclay to the N‐CNT/PVDF nanocomposite, which confirmed the dielectric results. Nitrogen heteroatoms (scattering centers) and functionalized nanoclay were responsible for reducing the dissipation factor.
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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".