Robust Displacement Sensing by Direct-Current Triboelectric Nanogenerator Via Intelligent Waveform Recognition

Keren Dai; Xuyi Miao; Wenling Zhang; Xiaohua Huang; He Zhang; Sang Woo Kim

doi:10.1002/advs.202204694

Robust Displacement Sensing by Direct-Current Triboelectric Nanogenerator Via Intelligent Waveform Recognition

Keren Dai, Xuyi Miao, Wenling Zhang, Xiaohua Huang, He Zhang, Sang Woo Kim

Department of Materials Science and Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

A triboelectric nanogenerator (TENG) facilitates the advancement of self-powered displacement sensors, which are important for many autonomous intelligent microsystems. However, the amplitude-based displacement sensing of conventional TENG-based sensors still suffers significantly from varying charge densities in harsh environments. Benefiting from the combination of intelligent signal processing algorithms and direct-current TENG sensors, this study proposes an environmentally robust character-based displacement sensing method that eliminates the influences of varying charge density in principle. The experimental results show that under drastically changing air humidity and other harsh environments, the sensing of threshold and maximum displacement has far superior consistency and stability than that of traditional amplitude-based TENG sensors, providing a novel route to realize reliable self-powered displacement sensing in environment-variable applications.

Original language	English
Article number	2204694
Journal	Advanced Science
Volume	10
Issue number	4
DOIs	https://doi.org/10.1002/advs.202204694
Publication status	Published - 2023 Feb 3

Bibliographical note

Funding Information:
K.D. and X.M. contributed equally to this work. This work was financially supported by the National Natural Science Foundation of China (Grant No. 52007084) and the Basic Science Research Program (2022R1A3B1078291) through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (MSIT) of Korea government.

Publisher Copyright:
© 2022 The Authors. Advanced Science published by Wiley-VCH GmbH.

All Science Journal Classification (ASJC) codes

Medicine (miscellaneous)
Chemical Engineering(all)
Materials Science(all)
Biochemistry, Genetics and Molecular Biology (miscellaneous)
Engineering(all)
Physics and Astronomy(all)

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title = "Robust Displacement Sensing by Direct-Current Triboelectric Nanogenerator Via Intelligent Waveform Recognition",

abstract = "A triboelectric nanogenerator (TENG) facilitates the advancement of self-powered displacement sensors, which are important for many autonomous intelligent microsystems. However, the amplitude-based displacement sensing of conventional TENG-based sensors still suffers significantly from varying charge densities in harsh environments. Benefiting from the combination of intelligent signal processing algorithms and direct-current TENG sensors, this study proposes an environmentally robust character-based displacement sensing method that eliminates the influences of varying charge density in principle. The experimental results show that under drastically changing air humidity and other harsh environments, the sensing of threshold and maximum displacement has far superior consistency and stability than that of traditional amplitude-based TENG sensors, providing a novel route to realize reliable self-powered displacement sensing in environment-variable applications.",

author = "Keren Dai and Xuyi Miao and Wenling Zhang and Xiaohua Huang and He Zhang and Kim, {Sang Woo}",

note = "Funding Information: K.D. and X.M. contributed equally to this work. This work was financially supported by the National Natural Science Foundation of China (Grant No. 52007084) and the Basic Science Research Program (2022R1A3B1078291) through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (MSIT) of Korea government. Publisher Copyright: {\textcopyright} 2022 The Authors. Advanced Science published by Wiley-VCH GmbH.",

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AU - Dai, Keren

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AU - Huang, Xiaohua

AU - Zhang, He

AU - Kim, Sang Woo

N1 - Funding Information: K.D. and X.M. contributed equally to this work. This work was financially supported by the National Natural Science Foundation of China (Grant No. 52007084) and the Basic Science Research Program (2022R1A3B1078291) through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (MSIT) of Korea government. Publisher Copyright: © 2022 The Authors. Advanced Science published by Wiley-VCH GmbH.

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N2 - A triboelectric nanogenerator (TENG) facilitates the advancement of self-powered displacement sensors, which are important for many autonomous intelligent microsystems. However, the amplitude-based displacement sensing of conventional TENG-based sensors still suffers significantly from varying charge densities in harsh environments. Benefiting from the combination of intelligent signal processing algorithms and direct-current TENG sensors, this study proposes an environmentally robust character-based displacement sensing method that eliminates the influences of varying charge density in principle. The experimental results show that under drastically changing air humidity and other harsh environments, the sensing of threshold and maximum displacement has far superior consistency and stability than that of traditional amplitude-based TENG sensors, providing a novel route to realize reliable self-powered displacement sensing in environment-variable applications.

AB - A triboelectric nanogenerator (TENG) facilitates the advancement of self-powered displacement sensors, which are important for many autonomous intelligent microsystems. However, the amplitude-based displacement sensing of conventional TENG-based sensors still suffers significantly from varying charge densities in harsh environments. Benefiting from the combination of intelligent signal processing algorithms and direct-current TENG sensors, this study proposes an environmentally robust character-based displacement sensing method that eliminates the influences of varying charge density in principle. The experimental results show that under drastically changing air humidity and other harsh environments, the sensing of threshold and maximum displacement has far superior consistency and stability than that of traditional amplitude-based TENG sensors, providing a novel route to realize reliable self-powered displacement sensing in environment-variable applications.

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Robust Displacement Sensing by Direct-Current Triboelectric Nanogenerator Via Intelligent Waveform Recognition

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