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High-performance strain sensors using flexible micro-porous 3D-graphene with conductive network synergy

  • Jinqiu Zhang
  • , Shanshui Lian
  • , Fanghao Zhu
  • , Genqiang Cao
  • , Hui Ma
  • , Bingkun Wang
  • , Huijuan Wu
  • , Ziqi Zhao
  • , Zhiduo Liu*
  • , Gang Wang*
  • *此作品的通讯作者
  • Ningbo University
  • CAS - Shanghai Institute of Microsystem and Information Technology

科研成果: 期刊稿件文章同行评审

摘要

Despite the advancement of flexible electronics, particularly wearable devices, soft robots, and human- machine interaction, flexible sensor designs have predominantly concentrated on uniaxial stimuli detection, which constrains their capability to discern the intricate multidimensional strains inherent in multi-degreeof- freedom motions. This study utilized plasma-enhanced chemical vapor deposition (PECVD) to in situ grow wafer-scale three-dimensional graphene (3D-graphene) on a silicon (Si) substrate, complemented by femtosecond laser cutting for precise patterning. The as-fabricated flexible strain sensor exhibits anisotropic electromechanical properties, driven by the porous and cross-linked nature of 3D-graphene, which significantly enhances the sensitivity and durability. Through tensile testing in both parallel and perpendicular orientations to the longitudinal axis of the graphene strip, distinct gauge factors (GF8 = 413 and GF> = 22) were observed, demonstrating the sensor's efficacy in the as-fabricated in-plane omnidirectional strain detection. Subsequent evaluations, including tensile, bending, and strain response tests, highlight exceptional performance characteristics: the sensor maintains integrity under 180-degree bending and demonstrates a rapid response time of 0.7 s. Such capabilities enable the sensor to monitor various human physiological activities across different scales, including eyelid blinks, facial muscle movements, respiratory cycles, and joint or cervical spine dynamics. This unique combination positions it as a promising candidate for next-generation wearable electronics and intelligent robotic systems.

源语言英语
页(从-至)3414-3423
页数10
期刊Journal of Materials Chemistry C
13
7
DOI
出版状态已出版 - 21 12月 2024

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