PVDF/Carbonnanotubes/Nanoclay Composites for Piezoelectric Applications
Bibliographic record
Abstract
Abstract Poly(vinylidene) fluoride (PVDF) nanocomposite samples were prepared by incorporation of carbon nanotubes (CNT) and nanoclay into PVDF using a twin screw extruder. Carbon nanotube was added to improve electrical conductivity and nanoclay was included to enhance β crystal formation for piezoelectric property. X-ray diffraction (XRD) results showed that partial melt intercalation of PVDF in clay was achieved. The XRD results also revealed that CNT and nanocaly addition increased β phase crystal amount in PVDF. FTIR spectroscopy measurements confirmed the XRD results and showed that the effect of nanoclay on β phase crystal formation of PVDF was more prominent than CNT. It was found that shear rate applied during crystallization would improve β phase crystal formation but only for the neat PVDF. Electrical conductivity results showed that addition of CNT improved conductivity as a percolation of 2 wt.% was observed. It was found that dispersion of CNT into PVDF matrix is very crucial for obtaining a higher conductivity. The results showed that clay incorporation into CNT nanocomposite improved electrical conductivity. The TEM micrographs showed bundles of CNT were adhered to clay particles. That was considered an indication of affinity between CNT and organically modified clay. The results of compounding of CNT and nanoclay with PVDF in batch mixer also revealed improvement in electrical conductivity when clay was added into PVDF/CNT composite in melt state. The conductivity improved with mixing time for both systems: PVDF/CNT and PVDF/CNT/nanocaly.
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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".