MXene‐Reinforced Cellulose Nanofibril Inks for 3D‐Printed Smart Fibres and Textiles

다국어 초록 (Multilingual Abstract)

Fibre‐based materials have received tremendous attention due to their flexibility and wearability. Although great efforts have been devoted to achieve high‐performance fibres over the past several years, it is still challenging for multifunctional macroscopic fibres to satisfy versatile applications. 2D transition metal carbides/nitrides (MXenes) with intriguing physical/chemical properties have been explored in broad application, and may be able to reinforce synthetic fibres. Inspired by natural materials, for the first time, flexible smart fibres and textiles are fabricated using a 3D printing process with hybrid inks of TEMPO (2,2,6,6‐tetramethylpiperidine‐1‐oxylradi‐cal)‐mediated oxidized cellulose nanofibrils (TOCNFs) and Ti3C2 MXene. The hybrid inks display good rheological properties, which allow them to achieve accurate structures and be rapidly printed. TOCNFs/Ti3C2 in hybrid inks self‐assemble to fibres with an aligned structure in ethanol, mimicking the features of the natural structures of plant fibres. In contrast to conventional synthetic fibres with limited functions, smart TOCNFs/Ti3C2 fibres and textiles exhibit significant responsiveness to multiple external stimuli (electrical/photonic/mechanical). TOCNFs/Ti3C2 textiles with electromechanical performance can be processed into sensitive strain sensors. Such multifunctional smart fibres and textiles will be promising in diverse applications, including wearable heating textiles, human health monitoring, and human–machine interfaces.
Highly flexible and conductive smart fibres and textiles with integrated multifunctionality are fabricated by assembling cellulose nanofibrils and Ti3C2 MXene using a facile 3D printing process. The resultant smart fibres and textiles exhibit excellent responsiveness to multiple external stimuli (electrical/photonic/mechanical). The smart textile can also be processed into a sensitive strain sensor to achieve real‐time human motion recognition.