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Smart Textiles for Energy Harvesting, Energy Conversion, Energy Storage and Multi-Mode Sensing

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Materials Science and Engineering".

Deadline for manuscript submissions: closed (25 July 2022) | Viewed by 1648

Special Issue Editors

Beijiing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China
Interests: smart textiles; fiber electronics; functional fabrics; triboelectric nanogenerators; energy harvesting and storage; self-powered sensing; biosensors; electronic skins; flexible electronics; human–machine interface

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Guest Editor
School of Textile Science and Engineering, Xi'an Polytechnic University, Xi'an 710048, China
Interests: structure–function textile composites; smart fiber and textile-based self-powered wearable sensors; protective and safety textiles; recycling of waste textiles
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Special Issue Information

Dear Colleagues,

Smart or electronic textiles that deliver electronic functionalities to the human body can collect, process, store, transmit, and display information in response to various environmental stimuli. Seamless integration of traditional textiles with advanced energy harvesting, energy conversion, energy storage, and multimode sensing technologies will provide versatile and wearable energy and sensing routes for distributed human-centered on-body electronics in the era of the Internet of Things and artificial intelligence. Functionalities endow textiles with power supply and sensing capabilities, while textiles provide a versatile flexible design carrier and extensive wearable application platform for their development. Smart textiles offer an inexpensive and convenient alternative with high breathability, wearing comfort, and scalability, which will attract considerable research interest and enrich a wide range of application areas ranging from wearable power sources, multifunctional sensors, and personized healthcare to humanoid robotics and human–machine interfaces.

With the aim to inspire future research activities and practical applications of smart textiles, this Special Issue focuses on fiber or fabric-based energy harvesting, energy conversion, energy storage, and multimode sensing devices, aiming to push forward the developments of these research directions from both fundamental fiber/textile science and related practical engineering issues.

Dr. Kai Dong
Dr. Wei Fan
Guest Editors

Manuscript Submission Information

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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. Applied Sciences 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 2400 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.

Published Papers (1 paper)

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Research

10 pages, 3470 KiB  
Article
Internal Damage Analysis of Braided Composites Embedded in Carbon Nanotube Yarn
by Minrui Jia and Zhenkai Wan
Appl. Sci. 2022, 12(1), 51; https://doi.org/10.3390/app12010051 - 22 Dec 2021
Cited by 2 | Viewed by 1014
Abstract
Carbon nanotube (CNT) yarn sensors were embedded in 3D braided composites in the form of arrays to detect the internal damage of specimens and study the internal damage monitoring of the 3D braided composites. The signals collected by the sensor array of CNT [...] Read more.
Carbon nanotube (CNT) yarn sensors were embedded in 3D braided composites in the form of arrays to detect the internal damage of specimens and study the internal damage monitoring of the 3D braided composites. The signals collected by the sensor array of CNT yarn were preprocessed using the dynamic wavelet threshold algorithm. The exact position of the damage was calculated based on the main features of the resistance signal matrix, which was calculated using the quadratic matrix singular value. The results show that the internal damage localization of the specimens was consistent with the actual damage. The localizations in this study can provide a basis for enhancing the structural health monitoring of smart 3D braided composites. Full article
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