Highly stretchable and sensitive flexible resistive strain sensor based on waterborne polyurethane polymer for wearable electronics
In recent years, flexible resistive sensors have attracted wide attention as one of the important components of wearable devices. However, it is difficult for most flexible sensors to have high stretchability and high sensitivity at the same time. In this study, the modified multi-walled carbon nano...
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Veröffentlicht in: | Composites science and technology 2022-04, Vol.221, p.109355, Article 109355 |
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Sprache: | eng |
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Zusammenfassung: | In recent years, flexible resistive sensors have attracted wide attention as one of the important components of wearable devices. However, it is difficult for most flexible sensors to have high stretchability and high sensitivity at the same time. In this study, the modified multi-walled carbon nanotubes as conductive fillers were filled into waterborne polyurethane to form conductive composites, leading to high stretchability of the sensor (120%). The regular crack structure was designed into the sensor to achieve a high gauge factor (∼2000), and the consistency of the sensor was realized by combining the screen-printing process. In addition, the flexible sensor has a short response time (90 ms), good long-term stability (>1000 cycles), and hysteresis characteristics. Furthermore, the excellent characteristics of the flexible sensor enabled it to have a wide working range for human motion and physiological detection, and the sensor was also successfully applied to Morse Code communication and human motion posture recognition for elder fall alarm. This provides a solution for applications in the field of medical health and human-computer interaction.
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•The strain sensor made by modified carbon nanotubes exhibits a wide strain range.•Double layer with regular cracks make the sensor has a high gauge factor.•Screen-printing with regular cracks make the sensor has a high consistency.•The sensor provides Morse Code communication and predict human movement to prevent falls. |
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ISSN: | 0266-3538 1879-1050 |
DOI: | 10.1016/j.compscitech.2022.109355 |