This study investigates the preparation, performance, and intelligent applications of a composite piezoelectric sensor based on polydimethylsiloxane (PDMS), zinc oxide (ZnO) nanoparticles, and graphene (Gr). The effects of different component ratios on the piezoelectric and mechanical properties of the material were systematically studied. The results showed that the maximum voltage reached 21.30 V when the PDMS:ZnO:Gr ratio was 5:2:0.3%, demonstrating excellent piezoelectric performance. Additionally, the influence of ZnO and Gr filling on the mechanical properties of the material was assessed, revealing a trade-off between piezoelectricity and flexibility. Scanning electron microscopy was used to characterize the morphology of the composites, providing insights into the dispersion of ZnO and Gr within the PDMS matrix. Furthermore, the developed piezoelectric sensor was explored for its potential in smart applications, including tactile pressure and frequency recognition, as well as tactile recognition based on convolutional neural networks. The sensor was able to detect and differentiate between various materials, demonstrating its feasibility for intelligent interaction and recognition systems. These findings lay a foundation for the development of high-performance, flexible piezoelectric sensors and open up new avenues for the application of piezoelectric materials in the field of intelligence.
1. Sekhar, M. C., Veena, E., Kumar, N. S., Naidu, K. C. B., Mallikarjuna, A. and Basha, D. B. A review on piezoelectric materials and their applications. Cryst. Res. Technol., 2023, 58(2), 2200130.
https://doi.org/10.1002/crat.202200130
2. Kim, K., Kim, J., Jiang, X. I. and Kim, T. Static force measurement using piezoelectric sensors. J. Sens. 2021, 2021, 6664200.
https://doi.org/10.1155/2021/6664200
3. Gao, X. Y., Yang, J. K., Wu, J. G., Xin, X. D., Li, Z. M., Yuan, X. T. et al. Piezoelectric actuators and motors: materials, designs, and applications. Adv. Mater. Technol., 2020, 5(1), 1900716.
https://doi.org/10.1002/admt.201900716
4. Toprak, A. and Tigli, O. Piezoelectric energy harvesting: state-of-the-art and challenges. Appl. Phys. Rev., 2014, 1(3), 031104.
https://doi.org/10.1063/1.4896166
5. Kögl, M. and Silva, E. C. N. Topology optimization of smart structures: design of piezoelectric plate and shell actuators. Smart Mater. Struct., 2005, 14(2), 387.
https://doi.org/10.1088/0964-1726/14/2/013
6. Amaechi, I. C., Youssef, A. H., Dörfler, A., González, Y., Katoch, R. and Ruediger, A. Catalytic applications of non-centrosymmetric oxide nanomaterials. Angew. Chem. Int. Edit., 2022, 61(43), e202207975.
https://doi.org/10.1002/anie.202207975
7. Zhang, N., Zheng, T. and Wu, J. Lead-free (K,Na)NbO3-based materials: preparation techniques and piezoelectricity. ACS Omega, 2020, 5(7), 3099–3107.
https://doi.org/10.1021/acso mega.9b03658
8. Wen, J., Wu, W., Xie, Z. and Wu, J. Development of piezoelectric elastomers and their applications in soft devices. Macromol. Mater. Eng., 2023, 308(11), 2300101.
https://doi.org/10.1002/mame.202300101
9. Chen, Y., Zhang, X. and Lu, C. Flexible piezoelectric materials and strain sensors for wearable electronics and artificial intelligence applications. Chem. Sci.,2024, 15(40), 16436–16466.
https://doi.org/10.1039/d4sc05166a
10. Berthier, E., Young, E. W. K. and Beebe, D. Engineers are from PDMS-land, biologists are from Polystyrenia. Lab Chip, 2012, 12(7), 1224–1237.
https://doi.org/10.1039/C2LC20982A
11. Kumar, B. and Kim, S.-W. Energy harvesting based on semiconducting piezoelectric ZnO nanostructures. Nano Energy, 2012, 1(3), 342–355.
https://doi.org/10.1016/j.nanoen.2012.02.001
12. Geim, A. K. Graphene: status and prospects. Science, 2009, 324(5934), 1530–1534.
https://doi.org/10.1126/science.1158877
13. Zhang, J., Jin, Z., Teng, S., Chen, G. and Bassir, D. Structural damage detection based on decision-level fusion with multi-vibration signals. Meas. Sci. Technol., 2022, 33(10), 105112.
https://doi.org/10.1088/1361-6501/ac7940
14. Yan, Z., Jin, Z., Teng, S., Chen, G. and Bassir, D. Measurement of bridge vibration by UAVs combined with CNN and KLT optical-flow method. Appl. Sci., 2022, 12(10), 5181.
https://doi.org/10.3390/app12105181
