journal article·2019-02

Stretchable strain sensor facilely fabricated based on multi-wall carbon nanotube composites with excellent performance

Xiang Fu, Maximiano Ramos, Ahmed M. Al-Jumaily, Ata Meshkinzar, Xiyong Huang

Journal of Materials Science· Volume 54· Issue 3
Publisher page

Abstract

In recent years, the increasing demand for flexible and wearable devices requires the synthesis of novel stretchable and piezoresistive materials. Piezoresistive polymer composites are popular due to their excellent piezoresistivity and high stretchability, which can readily be attached to clothes or human body. In this study, a stretchable and sensitive strain sensor based on multi-wall carbon nanotube (MWCNT)/polydimethylsiloxane (PDMS) composite with an excellent overall performance was fabricated in a facile and effective way. The composite with 7% MWCNTs is ideal for strain sensor compared to those with 5% and 9% MWCNTs. Not only can the gauge factor reach 5–9 under 10–40% strain, but also the curve of relative change in resistance versus strain is almost linear. The strain sensor can respond immediately with low hysteresis. The strain sensor also exhibits great stability under 1000 cycles of stretching/releasing, demonstrating the desirable long-term endurance to mechanical stimuli as well. The strain sensor was then implemented to monitor human motions (finger and wrist bending), precisely sensing the motion deformation and states. In conclusion, the reported sensor based on MWCNT/PDMS composite possesses numerous favorable characteristics including high sensitivity, good stretchability, ease of fabrication, and promising practical application in the field of biomedical system and wearable electronic devices.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Conducting polymers and applications · Muscle activation and electromyography studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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