MXene-based fibers: Preparation, applications, and prospects

被引:35
|
作者
Zhou, Yuxiao [1 ]
Zhang, Yali [1 ]
Ruan, Kunpeng [1 ]
Guo, Hua [1 ]
He, Mukun [1 ]
Qiu, Hua [1 ]
Gu, Junwei [1 ]
机构
[1] Northwestern Polytech Univ, Sch Chem & Chem Engn, Shaanxi Key Lab Macromol Sci & Technol, Xian 710072, Peoples R China
关键词
MXene-based fibers; Dispersion properties; Preparation techniques; Applications and prospects; MXENE/GRAPHENE HYBRID FIBERS; TITANIUM CARBIDE MXENE; GRAPHENE OXIDE; LIQUID-CRYSTALS; TI3C2TX MXENE; DISPERSIONS; FABRICATION; NANOFIBERS; FILMS;
D O I
10.1016/j.scib.2024.07.009
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
With the vigorous development and huge demand for portable wearable devices, wearable electronics based on functional fibers continue to emerge in a wide range of energy storage, motion monitoring, disease prevention, electromagnetic interference (EMI) shielding, etc. MXene, as an emerging twodimensional inorganic compound, has shown great potential in functional fiber manufacturing and has attracted much research attention due to its own good mechanical properties, high electrical conductivity, excellent electrochemical properties and favorable processability. Herein, this paper reviews recent advances of MXene-based fibers. Speaking to MXene dispersions, the properties of MXene dispersions including dispersion stability, rheological properties and liquid crystalline properties are highlighted. The preparation techniques used to produce MXene-based fibers and application progress regarding MXene-based fibers into supercapacitors, sensors, EMI shielding and Joule heaters are summarized. Challenges and prospects surrounding the development of MXene-based fibers are proposed in future. This review aims to provide processing guidelines for MXene-based fiber manufacturing, thereby achieving more possibilities of MXene-based fibers in advanced applications with a view to injecting more vitality into the field of smart wearables. (c) 2024 Science China Press. Published by Elsevier B.V. and Science China Press. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:2776 / 2792
页数:17
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