4.7 Article

High-Output Lotus-Leaf-Bionic Triboelectric Nanogenerators Based on 2D MXene for Health Monitoring of Human Feet

期刊

NANOMATERIALS
卷 12, 期 18, 页码 -

出版社

MDPI
DOI: 10.3390/nano12183217

关键词

triboelectric nanogenerator; MXene; graphene; energy harvesting; health monitoring

资金

  1. Natural Science Foundation of China [11865004]
  2. theNatural Science Foundation of Guangxi Zhuang Autonomous Region [2018GXNSFB A281163, 2018GXNSFAA281309]

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This study successfully produced high-output TENGs using a simple and low-cost lotus-leaf-bionic method. The performance of TENGs was evaluated by doping MXene and graphene into the structured PDMS. The results showed that the MXene-doped LLB TENGs had significantly higher output power and humidity sensitivity than graphene-doped devices, making them suitable for smart monitoring systems and health sensors.
As versatile energy harvesters, triboelectric nanogenerators (TENGs) have attracted considerable attention in developing portable and self-powered energy suppliers. The question of how to improve the output power of TENGs using cost-effective means is still under vigorous investigation. In this paper, high-output TENGs were successfully produced by using a simple and low-cost lotus-leaf-bionic (LLB) method. Well-distributed microstructures were fabricated via the LLB method on the surface of a polydimethylsiloxane (PDMS) negative triboelectric layer. 2D MXene (Ti3C2Tx) and graphene were doped into the structured PDMS to evaluate their effects on the performance of TENG. Owing to merits of the MXene doping and microstructures on the PDMS surface, the output power of MXene-doped LLB TENGs reached as high as 104.87 W/m(2), which was about 10 times higher than that of graphene-doped devices. The MXene-doped LLB TENGs can be used as humidity sensors, with a sensitivity of 4.4 V per RH%. In addition, the MXene-doped LLB TENGs were also sensitive to human body motions; hence, a foot health monitoring system constructed by the MXene-doped LLB TENGs was successfully demonstrated. The results in this work introduce a way to produce cost-effective TENGs using bionic means and suggest the promising applications of TENGs in the smart monitoring system of human health.

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