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Special Issue "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: 31 January 2022.

Special Issue Editors

Prof. Dr. Chi Zhang
E-Mail Website
Guest Editor
Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China
Interests: nanogenerator; self-powered MEMS/NEMS; tribotronics; triboelectric powertech
Prof. Dr. Hao Wu
E-Mail Website
Guest Editor
School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, 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

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

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

Published Papers (3 papers)

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Research

Article
Texture Recognition Based on Perception Data from a Bionic Tactile Sensor
Sensors 2021, 21(15), 5224; https://doi.org/10.3390/s21155224 - 02 Aug 2021
Viewed by 439
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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Communication
An Effective Self-Powered Piezoelectric Sensor for Monitoring Basketball Skills
Sensors 2021, 21(15), 5144; https://doi.org/10.3390/s21155144 - 29 Jul 2021
Viewed by 394
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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Communication
A Tubular Flexible Triboelectric Nanogenerator with a Superhydrophobic Surface for Human Motion Detecting
Sensors 2021, 21(11), 3634; https://doi.org/10.3390/s21113634 - 23 May 2021
Cited by 1 | Viewed by 829
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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