基于聚酰胺弹性体/BaTiO3的自供电无线压电传感器用于机器学习辅助人体运动监测。

IF 8.2 2区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Weifang Zhou,Zhihao Chen,Xin Yuan,Hui Yu,Yuancheng Zhang,Wei Zhao,Xin Li,Xiaomeng Zhang,Zhe Cui,Peng Fu,Xinchang Pang,Minying Liu
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引用次数: 0

摘要

在自供电传感领域,对材料的穿着舒适性和柔韧性的要求越来越高。压电陶瓷虽然具有优异的压电性能,但其较差的柔韧性限制了其应用范围。为了追求更好的穿着舒适性,以弹性体为聚合物基体的纳米复合聚合物正在迅速兴起。然而,由于纳米填料表面能的显著差异,在聚合物基体中实现均匀分散仍然是一个挑战。本文通过将γ-氨基丙基三乙氧基硅烷(KH550)功能化的BaTiO3纳米粒子(KH550@BTO)加入到具有传感能力的柔性压电纳米发电装置(PENGs)的TPAE原位缩聚中,提出了一种具有强界面强度和均匀分散的新型热塑性聚酰胺弹性体(TPAE)纳米复合材料。peng不仅具有优异的力学性能(断裂伸长率~ 400%),而且具有良好的压电性能(VOC ~ 19 V, ISC ~ 121 nA)。此外,peng具有优异的耐久性,稳定性(6000次循环而不降解)和快速响应时间(~ 21 ms),优于大多数报道的bto基纳米复合材料。基于该性能,在无线可穿戴设备组装完成后,PENG可用于监测人体运动,并在机器学习的辅助下进一步识别不同的羽毛球发球姿势。本研究为柔性压电纳米复合材料的制备提供了一种创新的方法,有助于实现性能更好、使用更舒适的自供电无线柔性传感器,用于人体运动监测和识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Self-Powered Wireless Piezoelectric Sensor Based on Polyamide Elastomer/BaTiO3 for Machine Learning-Assisted Human Motion Monitoring.
In the field of self-powered sensing, the need for wearing comfort and flexibility of the material is increasing. Although piezoelectric ceramics have excellent piezoelectric properties, their poor flexibility limits their application range. In the quest for better wearing comfort, nanocomposite polymers using elastomers as polymer matrices are rapidly emerging. However, there still exists a challenge to achieve uniform dispersion of nanofillers in the polymer matrix due to their significant difference in surface energy. In this work, a novel thermoplastic polyamide elastomer (TPAE) based nanocomposite with strong interfacial strength and uniform dispersion was proposed, which was achieved through incorporating γ-aminopropyltriethoxysilane (KH550)-functionalized BaTiO3 nanoparticles (KH550@BTO) into in situ polycondensation of TPAE for flexible piezoelectric nanogenerators (PENGs) with sensing capability. The PENGs not only possessed excellent mechanical properties (elongation at break ∼ 400%) but also exhibited good piezoelectric behavior (VOC ∼ 19 V, ISC ∼ 121 nA). Moreover, the PENGs exhibited excellent durability, stability (6000 cycles without degradation), and rapid response time (∼21 ms), which was superior to those of most reported BTO-based nanocomposites. Based on the performance, the PENG could be used to monitor human motions after the assembly of wireless wearable devices, and different badminton serving postures were further recognized by the assistance of machine learning. This work provides an innovative approach for the preparation of soft piezoelectric nanocomposites, which is helpful for self-powered and wireless flexible sensors with better performance and more comfortable use in human motion monitoring and recognition.
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来源期刊
ACS Applied Materials & Interfaces
ACS Applied Materials & Interfaces 工程技术-材料科学:综合
CiteScore
16.00
自引率
6.30%
发文量
4978
审稿时长
1.8 months
期刊介绍: ACS Applied Materials & Interfaces is a leading interdisciplinary journal that brings together chemists, engineers, physicists, and biologists to explore the development and utilization of newly-discovered materials and interfacial processes for specific applications. Our journal has experienced remarkable growth since its establishment in 2009, both in terms of the number of articles published and the impact of the research showcased. We are proud to foster a truly global community, with the majority of published articles originating from outside the United States, reflecting the rapid growth of applied research worldwide.
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