现代纺织技术 ›› 2023, Vol. 31 ›› Issue (5): 22-29.

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rGO/MWCNT/PDMS复合柔性压力传感器的制备与性能#br#

  

  1. 1.国家知识产权局专利局专利审查协作江苏中心,江苏苏州215163; 2.苏州大学纺织与服装工程学院,江苏苏州215021
  • 收稿日期:2022-11-11 出版日期:2023-09-10 网络出版日期:2023-09-20
  • 作者简介:陈岭(1985—),女,湖北孝感人,副研究员,硕士,主要从事功能与智能纤维材料及器件方面的研究。
  • 基金资助:
    苏州市重点产业技术创新前瞻性应用研究项目(SYG201936)

Preparation and properties of rGO/MWCNT/PDMS composite flexible pressure sensors

  1. 1. Patent Examination Cooperation (Jiangsu) Center of the Patent Office, CNIPA, Suzhou 215163, China; 2. College of Textile and Clothing Engineering, Soochow University, Suzhou215021, China
  • Received:2022-11-11 Published:2023-09-10 Online:2023-09-20

摘要: 为开发具有较高灵敏度和稳定性的电容式柔性压力传感器,以聚二甲基硅氧烷(PDMS)为基体,通过方糖颗粒造孔,并掺杂多壁碳纳米管(MWCNT)和还原氧化石墨烯(rGO),制备了rGO/MWCNT/PDMS多孔复合柔性压力传感器。比较研究了单一掺杂MWCNT和复合掺杂对提升传感器灵敏度的作用,分析了不同掺杂后PDMS多孔海绵的结构以及掺杂含量对灵敏度的影响,测试了传感器的响应时间、迟滞性、循环稳定性等关键传感特性,探讨了其在智能可穿戴纺织品中的应用可行性。结果表明:添加rGO的共混掺杂能够有效改善MWCNT掺杂时的团聚问题,保持PDMS基海绵的多孔结构,并有效提升了压力传感器的灵敏度。当MWCNT与rGO质量比为1∶1,掺杂含量为2.5%时,rGO/MWCNT/PDMS复合柔性压力传感器的灵敏度最高,在0~0.5 kPa压强范围内的灵敏度达到了31.324 kPa-1,是纯PDMS的4倍多。同时,该柔性压力传感器还表现出较快的响应时间,极小的迟滞误差,良好的循环稳定性和力学稳定性。利用该柔性压力传感器所设计的智能鞋垫对不同脚部压力作用表现出良好的响应反馈,展现出其在智能可穿戴产品中的广阔应用前景。

关键词: 压力传感器, 聚二甲基硅氧烷, 多壁碳纳米管, 还原氧化石墨烯

Abstract: With the rapid development of the wearable electronic device industry all over the word, the related products have shown great commercial prospects. As the future growing trend of wearable electronic devices, flexible wearable electronics has gradually become the focus of research and application in various fields, especially in the textile field. Among them, as a key component of information interaction, the flexible pressure sensor has attracted much attention due to its broad application prospects in health detection, electronic skin, human-computer interaction, flexible touch screen and other fields. According to its sensing mechanism, flexible pressure sensors are generally divided into piezoresistive, capacitive and piezoelectric ones. In practical applications, sensitivity and stability are the key technical indicators of flexible pressure sensors.
In order to develop a flexible pressure sensor with high sensitivity and excellent stability, a composite porous capacitive flexible pressure sensor was prepared in this research with polydimethylsiloxane (PDMS) as the substrate, multi-wall carbon nanotubes (MWCNT) and reduced graphene oxide (rGO) as fillers. And the porous structure was formed through sugar particle template. The effects of single doping with MWCNT and composite doping with MWCNT and rGO on the sensitivity of the sensor were compared. The structure of PDMS sponge after doping in different ways and the influence of the doping concentration on the sensitivity were analyzed. The key sensing characteristics of the sensor, such as response time, hysteresis and cycle stability were tested. The feasibility of its application in intelligent wearable textiles was discussed. The results show that the blending doping with rGO can effectively improve the aggregation of MWCNT, improve the dispersible uniformity of the doped conductive medium, maintain the porous structure of PDMS sponge, and effectively improve the sensitivity of the pressure sensor. When the mass ratio of MWCNT to rGO is 1:1 and the doping concentration is 2.5%, the sensitivity of the rGO/MWCNT/PDMS composite flexible pressure sensor reaches the highest value. The sensitivity reaches 31.324 kPa-1 in the pressure range of 0~0.5 kPa, which is more than four times of the pure PDMS sponge, and more than twice of mono-doped MWCNT with the same mass ratio. At the same time, the flexible pressure sensor also shows fast response, minimal hysteresis error, good cycle stability and mechanical stability. The strain-stress curves of 300 and 500 cycles of cyclic compression at 30% deformation are basically consistent.
The intelligent insole designed and prepared by using the flexible pressure sensor shows good response feedback to different foot pressures, which can be used in intelligent sports shoes as a flexible pressure sensor unit for recording and analyzing athletes' running posture data, showing a broad application prospect in intelligent wearable products.

Key words: pressure sensor, PDMS, MWCNT, rGO

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