The tunable sensing behaviors of flexible conductive PDMS/NCG composites via regulation of filler size prepared by a facile sedimentation method
Composites Science and Technology, ISSN: 0266-3538, Vol: 216, Page: 109037
2021
- 6Citations
- 5Captures
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Article Description
Flexible strain sensing composites with tunable behaviors are widely required in fields such as telemedicine, wearable health monitoring equipment, and electronic skin. In this study, the sensing behaviors of flexible conductive polydimethylsiloxane (PDMS)/nickel-coated graphite (NCG) composites were easily regulated by adjusting the NCG size, in which the composites were prepared by a facile sedimentation method. The size of NCG particles has a significant impact on the sensing performances, including resistance change against strain and working range. When the size was small (1 and 30 μm), the resistance of PDMS/NCG slightly increased, then decreased clearly, and finally rose with increasing strain again. On the other hand, the resistance of PDMS/NCG increased monotonously with strain when the size was large (80 and 100 μm). The working range decreased with increments of filler size. Then, resistance of composites against strain was easily tuned by changing the content ratio of hybrid fillers with NCG of 30 μm and 100 μm. It was due to the competition between the resistance change along and perpendicular to the stretching direction which was proved by the morphology revolution and sensing performance of composites with hybrid fillers. The composite sensors could realize the detection of human motion. The results show that the controls of filler size and synergy effects of the hybrid fillers with different sizes are efficient ways to regulate the sensing behaviors of flexible sensors.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0266353821003936; http://dx.doi.org/10.1016/j.compscitech.2021.109037; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85115303343&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0266353821003936; https://dx.doi.org/10.1016/j.compscitech.2021.109037
Elsevier BV
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