One-Step Solvent Evaporation-Assisted 3D Printing of Piezoelectric PVDF Nanocomposite Structures
Bibliographic record
Abstract
Development of a 3D printable material system possessing inherent piezoelectric properties to fabricate integrable sensors in a single-step printing process without poling is of importance to the creation of a wide variety of smart structures. Here, we study the effect of addition of barium titanate nanoparticles in nucleating piezoelectric β-polymorph in 3D printable polyvinylidene fluoride (PVDF) and fabrication of the layer-by-layer and self-supporting piezoelectric structures on a micro- to millimeter scale by solvent evaporation-assisted 3D printing at room temperature. The nanocomposite formulation obtained after a comprehensive investigation of composition and processing techniques possesses a piezoelectric coefficient, d 31, of 18 pC N –1, which is comparable to that of typical poled and stretched commercial PVDF film sensors. A 3D contact sensor that generates up to 4 V upon gentle finger taps demonstrates the efficacy of the fabrication technique. Our one-step 3D printing of piezoelectric nanocomposites can form ready-to-use, complex-shaped, flexible, and lightweight piezoelectric devices. When combined with other 3D printable materials, they could serve as stand-alone or embedded sensors in aerospace, biomedicine, and robotic applications.
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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".