Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/156191
Title: Self-powered multifunctional sensing based on super-elastic fibers by soluble-core thermal drawing
Authors: Chen, Mengxiao
Wang, Zhe
Zhang, Qichong
Wang, Zhixun
Liu, Wei
Chen, Ming
Wei, Lei
Keywords: Engineering::Materials::Functional materials
Issue Date: 2021
Source: Chen, M., Wang, Z., Zhang, Q., Wang, Z., Liu, W., Chen, M. & Wei, L. (2021). Self-powered multifunctional sensing based on super-elastic fibers by soluble-core thermal drawing. Nature Communications, 12(1), 1416-. https://dx.doi.org/10.1038/s41467-021-21729-9
Project: MOE2019-T2-2-127 
MOE T2EP50120-0005
A*STAR A2083c0062
MOE RG90/19
MOE RG73/19
NRF-CRP18-2017-02
Journal: Nature Communications
Abstract: The well-developed preform-to-fiber thermal drawing technique owns the benefit to maintain the cross-section architecture and obtain an individual micro-scale strand of fiber with the extended length up to thousand meters. In this work, we propose and demonstrate a two-step soluble-core fabrication method by combining such an inherently scalable manufacturing method with simple post-draw processing to explore the low viscosity polymer fibers and the potential of soft fiber electronics. As a result, an ultra-stretchable conductive fiber is achieved, which maintains excellent conductivity even under 1900% strain or 1.5 kg load/impact freefalling from 0.8-m height. Moreover, by combining with triboelectric nanogenerator technique, this fiber acts as a self-powered self-adapting multi-dimensional sensor attached on sports gears to monitor sports performance while bearing sudden impacts. Next, owing to its remarkable waterproof and easy packaging properties, this fiber detector can sense different ion movements in various solutions, revealing the promising applications for large-area undersea detection.
URI: https://hdl.handle.net/10356/156191
ISSN: 2041-1723
DOI: 10.1038/s41467-021-21729-9
Schools: School of Electrical and Electronic Engineering 
Research Centres: CNRS International NTU THALES Research Alliances 
Rights: © 2021 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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