Sol-gel hydrothermal synthesis of lead-free BT nanoparticles for enhanced dielectric properties in PVDF nanocomposites
Bibliographic record
Abstract
In the present work BaTiO3 nanoparticles (NPs) with different sizes from 150 to 400 nm were prepared by sol–gel hydrothermal method at a temperature lower than 220 °C, and were used as nanofiller for PVDF composites with a loading from 10 to 25 vol%. The morphology of the BT NPs was analyzed by Scanning Electron Microscopy (SEM), and the structural composition was studied by Raman spectroscopy and X-ray diffraction (XRD). The hydrothermal temperature was found to control both the size as well as the phase composition of the BT NPs. The PVDF/BT nanocomposites exhibit enhanced dielectric permittivity and reduced loss tangent , especially with 20 vol% NPs, which contributes to the improvement of the ferroelectric properties . The inclusion of BT in PVDF matrix enhances also the crystallinity of PVDF by acting as a nucleating agent , which further increases the stiffness of the composite. However, at higher volume loading, the reverse tendency was observed with a huge decrease in the PVDF crystallinity at 25 vol%. The simulated PE loop was also investigated for the different loadings mentioned above using an Ising type model based on a 2D lattice and solved by monte-Carlo metropolis method. The results are in good agreement with the experimental results for the polarization hysteresis loops .
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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 | 0.001 |
| 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".