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Micro/Nano Energy and Flexible Sensors

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 21923

Special Issue Editors

Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China
Interests: nanogenerators; self-powered MEMS/NEMS; tribotronics; triboelectric powertech
School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
Interests: flexible electronic devices and integration; robotic perception; Human-computer interaction; wearable healthcare

Special Issue Information

Dear Colleagues,

Flexible electronics is a multidisciplinary research frontier involving chemistry, material science, engineering, medicine and so on. With the development of Internet of Things technology, flexible electronic devices have a broad application prospect in the fields of human health, wearable electronics and robotics. Many kinds of flexible electronic devices have been distributed all over the world. The traditional energy supply for flexible electronic devices by chemical batteries is high cost and contributes to environmental pollution. With the growing threat of energy crises and pollution, the search for renewable energy is one of the most urgent challenges for the sustainable development of human civilization. Micro/nano energy is a kind of sustained, maintenance-free, self-powered energy for flexible electronic devices. Micro/nano energy technology is expected to provide a complete micro energy solution for widely distributed flexible electronic devices. The combination of micro/nano energy utilization technology and flexible electronics promotes the development of miniaturization and intelligence of electronic devices and systems. Therefore, the research of micro/nano energy technology and flexible electronics is important for the development of the Internet of Things. Sensors encourages the research of micro/nano energy technology and flexible electronics.

Prof. Dr. Chi Zhang
Prof. Dr. Hao Wu
Guest Editors

Manuscript Submission Information

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Keywords

  • micro/nano energy
  • flexible electronics
  • self-powered system
  • internet of things
  • sustainable energy supply
  • self-powered sensing

Published Papers (5 papers)

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Research

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15 pages, 4056 KiB  
Article
Texture Recognition Based on Perception Data from a Bionic Tactile Sensor
by Shiyao Huang and Hao Wu
Sensors 2021, 21(15), 5224; https://0-doi-org.brum.beds.ac.uk/10.3390/s21155224 - 02 Aug 2021
Cited by 21 | Viewed by 3704
Abstract
Texture recognition is important for robots to discern the characteristics of the object surface and adjust grasping and manipulation strategies accordingly. It is still challenging to develop texture classification approaches that are accurate and do not require high computational costs. In this work, [...] Read more.
Texture recognition is important for robots to discern the characteristics of the object surface and adjust grasping and manipulation strategies accordingly. It is still challenging to develop texture classification approaches that are accurate and do not require high computational costs. In this work, we adopt a bionic tactile sensor to collect vibration data while sliding against materials of interest. Under a fixed contact pressure and speed, a total of 1000 sets of vibration data from ten different materials were collected. With the tactile perception data, four types of texture recognition algorithms are proposed. Three machine learning algorithms, including support vector machine, random forest, and K-nearest neighbor, are established for texture recognition. The test accuracy of those three methods are 95%, 94%, 94%, respectively. In the detection process of machine learning algorithms, the asamoto and polyester are easy to be confused with each other. A convolutional neural network is established to further increase the test accuracy to 98.5%. The three machine learning models and convolutional neural network demonstrate high accuracy and excellent robustness. Full article
(This article belongs to the Special Issue Micro/Nano Energy and Flexible Sensors)
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12 pages, 6013 KiB  
Communication
An Effective Self-Powered Piezoelectric Sensor for Monitoring Basketball Skills
by Chongle Zhao, Changjun Jia, Yongsheng Zhu and Tianming Zhao
Sensors 2021, 21(15), 5144; https://0-doi-org.brum.beds.ac.uk/10.3390/s21155144 - 29 Jul 2021
Cited by 13 | Viewed by 2554
Abstract
Self-powered piezoelectric sensor can achieve real-time and harmless monitoring of motion processes without external power supply, which can be attached on body skin or joints to detect human motion and powered by mechanical energy. Here, a sensor for monitoring emergent motion is developed [...] Read more.
Self-powered piezoelectric sensor can achieve real-time and harmless monitoring of motion processes without external power supply, which can be attached on body skin or joints to detect human motion and powered by mechanical energy. Here, a sensor for monitoring emergent motion is developed using the PVDF as active material and piezoelectric output as sensing signal. The multi-point control function enables the sensor to monitor the sequence of force order, angle change, and motion frequency of the “elbow lift, arm extension, and wrist compression” during shooting basketball. In addition, the sensor shows can simultaneously charge the capacitor to provide more power for intelligence, typically Bluetooth transmission. The sensor shows good performance in other field, such as rehabilitation monitoring and speech input systems. Therefore, the emerging application of flexible sensors have huge long-term prospects in sport big data collection and Internet of Things (IoT). Full article
(This article belongs to the Special Issue Micro/Nano Energy and Flexible Sensors)
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11 pages, 5870 KiB  
Communication
A Tubular Flexible Triboelectric Nanogenerator with a Superhydrophobic Surface for Human Motion Detecting
by Jianwei Wang, Zhizhen Zhao, Xiangwen Zeng, Xiyu Liu and Youfan Hu
Sensors 2021, 21(11), 3634; https://0-doi-org.brum.beds.ac.uk/10.3390/s21113634 - 23 May 2021
Cited by 12 | Viewed by 3029
Abstract
The triboelectric nanogenerator (TENG) is a newly arisen technology for mechanical energy harvesting from the environment, such as raindrops, wind, tides, and so on. It has attracted widespread attention in flexible electronics to serve as self-powered sensors and energy-harvesting devices because of its [...] Read more.
The triboelectric nanogenerator (TENG) is a newly arisen technology for mechanical energy harvesting from the environment, such as raindrops, wind, tides, and so on. It has attracted widespread attention in flexible electronics to serve as self-powered sensors and energy-harvesting devices because of its flexibility, durability, adaptability, and multi-functionalities. In this work, we fabricated a tubular flexible triboelectric nanogenerator (TF-TENG) with energy harvesting and human motion monitoring capabilities by employing polydimethylsiloxane (PDMS) as construction material, and fluorinated ethylene propylene (FEP) films coated with Cu as the triboelectric layer and electrode, serving in a free-standing mode. The tube structure has excellent stretchability that can be stretched up to 400%. Modifying the FEP films to obtain a superhydrophobic surface, the output performance of TF-TENG was increased by at least 100% compared to an untreated one. Finally, as the output of TF-TENG is sensitive to swing angle and frequency, demonstration of real-time monitoring of human motion state was realized when a TF-TENG was worn on the wrist. Full article
(This article belongs to the Special Issue Micro/Nano Energy and Flexible Sensors)
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Review

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23 pages, 39907 KiB  
Review
Recent Progress of Switching Power Management for Triboelectric Nanogenerators
by Han Zhou, Guoxu Liu, Jianhua Zeng, Yiming Dai, Weilin Zhou, Chongyong Xiao, Tianrui Dang, Wenbo Yu, Yuanfen Chen and Chi Zhang
Sensors 2022, 22(4), 1668; https://0-doi-org.brum.beds.ac.uk/10.3390/s22041668 - 21 Feb 2022
Cited by 13 | Viewed by 4560
Abstract
Based on the coupling effect of contact electrification and electrostatic induction, the triboelectric nanogenerator (TENG) as an emerging energy technology can effectively harvest mechanical energy from the ambient environment. However, due to its inherent property of large impedance, the TENG shows high voltage, [...] Read more.
Based on the coupling effect of contact electrification and electrostatic induction, the triboelectric nanogenerator (TENG) as an emerging energy technology can effectively harvest mechanical energy from the ambient environment. However, due to its inherent property of large impedance, the TENG shows high voltage, low current and limited output power, which cannot satisfy the stable power supply requirements of conventional electronics. As the interface unit between the TENG and load devices, the power management circuit can perform significant functions of voltage and impedance conversion for efficient energy supply and storage. Here, a review of the recent progress of switching power management for TENGs is introduced. Firstly, the fundamentals of the TENG are briefly introduced. Secondly, according to the switch types, the existing power management methods are summarized and divided into four categories: travel switch, voltage trigger switch, transistor switch of discrete components and integrated circuit switch. The switch structure and power management principle of each type are reviewed in detail. Finally, the advantages and drawbacks of various switching power management circuits for TENGs are systematically summarized, and the challenges and development of further research are prospected. Full article
(This article belongs to the Special Issue Micro/Nano Energy and Flexible Sensors)
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26 pages, 5814 KiB  
Review
Triboelectric Nanogenerators as Active Tactile Stimulators for Multifunctional Sensing and Artificial Synapses
by Jianhua Zeng, Junqing Zhao, Chengxi Li, Youchao Qi, Guoxu Liu, Xianpeng Fu, Han Zhou and Chi Zhang
Sensors 2022, 22(3), 975; https://0-doi-org.brum.beds.ac.uk/10.3390/s22030975 - 27 Jan 2022
Cited by 14 | Viewed by 6258
Abstract
The wearable tactile sensors have attracted great attention in the fields of intelligent robots, healthcare monitors and human-machine interactions. To create active tactile sensors that can directly generate electrical signals in response to stimuli from the surrounding environment is of great significance. Triboelectric [...] Read more.
The wearable tactile sensors have attracted great attention in the fields of intelligent robots, healthcare monitors and human-machine interactions. To create active tactile sensors that can directly generate electrical signals in response to stimuli from the surrounding environment is of great significance. Triboelectric nanogenerators (TENGs) have the advantages of high sensitivity, fast response speed and low cost that can convert any type of mechanical motion in the surrounding environment into electrical signals, which provides an effective strategy to design the self-powered active tactile sensors. Here, an overview of the development in TENGs as tactile stimulators for multifunctional sensing and artificial synapses is systematically introduced. Firstly, the applications of TENGs as tactile stimulators in pressure, temperature, proximity sensing, and object recognition are introduced in detail. Then, the research progress of TENGs as tactile stimulators for artificial synapses is emphatically introduced, which is mainly reflected in the electrolyte-gate synaptic transistors, optoelectronic synaptic transistors, floating-gate synaptic transistors, reduced graphene oxides-based artificial synapse, and integrated circuit-based artificial synapse and nervous systems. Finally, the challenges of TENGs as tactile stimulators for multifunctional sensing and artificial synapses in practical applications are summarized, and the future development prospects are expected. Full article
(This article belongs to the Special Issue Micro/Nano Energy and Flexible Sensors)
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