Nanoparticle and Process Induced Super Toughened Piezoelectric Hybrid Materials: The Effect of Stretching on Filled System
Bibliographic record
Abstract
Process and nanoparticle induced piezoelectric super toughened poly(vinylidene fluoride) (PVDF) nanohybrids have been demonstrated. The nanohybrids have been prepared by incorporating organically modified nanoclay through melt extrusion and solution route. The solution processed nanohybrid exhibit 1100% improvement in toughness as well as adequate stiffness as compared to pure PVDF without any trade-off. The structural and morphological origins of super toughening phenomena have been worked out. The unique crystallization behavior of PVDF on top of the silicate layers (β-phase, planar zigzag chain conformation, and subsequent polar γ-phase and α-phase as layered type) has been revealed to create an island type of structure, which in turn is responsible for greater toughness. The extent of piezoelectric β-phase has been enhanced by controlled stretching of the nanohybrid at moderately high temperature for better disentanglement, and 90% of the piezoelectric phase has been stabilized. The structural change over has been confirmed through XRD, FTIR, and DSC studies. The nanohybrids possess β-phase with a small amount of α-phase and distorted γ-phase (T 3 G-T 6 G) before stretching which convert into predominantly β-phase with increasing the draw ratio, whereas pure PVDF converted directly into β-phase from pure α-phase. The piezoelectric coefficient ( d 33 ) exhibits significant increase with draw ratio, and the relative enhancement is more in nanohybrid vis-à-vis pure PVDF arising from the presence of greater β-phase leading to super toughened lightweight piezoelectric material.
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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".