Dynamic interfacial cross-linking and chain entanglement enabling robust mechanical and conductive TPU composite fibers for knitted wearable strain sensors

Abstract

Integrating conductive materials into elastomeric fibers as wearable and knittable sensors has recently attained extensive attention. However, the poor interfacial adhesion between them results in the formation of continuous and directional conductive pathways, leading to suboptimal electrical performance and mechanical robustness, thereby hindering their large-scale production. This study explored how dynamic interfacial cross-linking and chain entanglement could enhance thermoplastic polyurethane (TPU) composite fibers, which incorporated continuous conductive nanochannels interwoven with a cross-linked polymeric framework. The TPU composite fibers were composed of gallic acid/hexamethylene diamine (GAHD), single-walled carbon nanotubes modified with 2,2-dihydroxymethylpropionic acid (SWCNT–DMPA), TPU, Ti₃C₂T_x MXene, poly(3,4-ethylenedioxythiophene) (PEDOT), and silver nanoparticles (AgNPs). These fibers, abbreviated as GCTMP–Ag composite fibers, were fabricated using a scalable wet-spinning technique. The oxyanion-enriched terminations of the conductive nanocomposites facilitated the enhancement of dynamic interfacial cross-linking interactions while promoting the formation of a chain-entangled structure within the fibers. The reasonable design of the conductive nanocomposites enabled the GCTMP–Ag composite fibers to exhibit superior electrical properties with a sensing performance (gauge factor = 4257.25), an extensive deformation range (1–800%), and mechanical robustness. Remarkably, they were successfully knitted on a knitting machine to monitor comprehensive human-body movements. More significantly, these fabricated knitted fabrics presented remarkable stability under various deformations, a rapid response (29 ms), exceptional electromagnetic interference shielding, and durability for over 1000 cycles (at 160% strain). This study presents a practical approach for prospective applications in wearable motion detection systems.