Construction Of Cellulose-based Smart Yarns Assisted By Solvent-welding Method

With the increasing scarcity of petroleum resources and the deepening of environmental protection,the focus of researchers has gradually shifted from petroleum-based polymer materials to bio-based materials,which are not only widely available,biodegradable and renewable,but also have excellent mechanical properties and skin affinity.Cellulose is the most abundant bio-based polymer and is highly valuable due to its low cost,renewable,easy processing,biodegradability,dielectric properties,piezoelectricity and excellent mechanical property.Cellulosic materials include cellulose fibers,cellulose films,and cellulose aerogels,among which cellulose fibers,as one-dimensional materials,are more expansive and can not only be directly applied in textiles by twisting,sewing,and weaving techniques,but also construct two-dimensional,three-dimensional,or functional materials by bottom-up strategies.The application fields of all-cellulose fibers are limited due to their single performance.Therefore,the multifunctionality of cellulose-based fibers should be expanded and designed.Textile-based wearable electronics can combine conductive functionality with wearable comfort,which is one of the important development directions for advanced electron devices.Conductive fibers/yarns are typical representatives for building textile-based wearable electronic devices,among which cellulose-based smart fibers/yarns become key research materials of future electronic devices due to the biocompatible,eco-friendly and low-cost features.Here,we developed a solvent-welding technique for cotton yarns using aqueous phosphoric acid and explored the effect of process parameters（different temperatures of impregnation and dissolution）on the self-reinforced welding effect of cotton yarns.The physicochemical properties of all-cellulose welded yarns were tested and characterized in terms of surface morphology,mechanical properties,crystallinity,dyeing properties,and pilling resistance.The results showed that the best tensile strength increment（128.2%）was obtained for welded yarns,which made by infiltrating the yarns with the solvent at room temperature and dissolving at-18°C.The welding effect was retained stably in the subsequent dyeing process,and the welded yarns could obtain a better dyeing depth than the original cotton yarns in the same dyeing process due to the increased amorphous area on their surface.In addition,the welding process reduces the hairiness on the surface of the yarn,and the woven fabric shows excellent anti-pilling performance in the round track friction test.The above solvent welding technique is functionally expandable and can be further applied to the preparation of conductive welded yarns.In this work,with the assistance of pre-dissolved microcrystalline cellulose,the conductive welding dopes were obtained by uniformly dispersing carbon nanotubes（CNT）into aqueous phosphoric acid.The homogeneous dispersion of CNT in the welding dope was characterized by optical microscope,transmission electron microscope,and Raman spectroscopy tests;the multiple weak molecular interactions between cellulose and CNT were demonstrated by molecular dynamic simulation.The highly conductive cellulose/CNT welded yarns were prepared through a functional welding process,and the application performances of the yarns were tested and characterized in terms of mechanical properties,conductivity,washability and weavability.The results showed that the cellulose/CNT welded yarn could achieve a tensile strength increment of 77.9%higher than the pristine cotton yarns,a conductivity of 334.6 S m^-1at a relatively low CNT loading（11.2 wt%）,and excellent wash-fastness in the temperature range of 30–80°C.The welded yarns were eventually woven into fabrics to verify their sensitive responsibility to environmental solvents and moisture as well as their ability to detect behavioral motions and physiological electrical signals in the human body,which were integrated into a wearable multi-module sensing system for applications in respiratory health monitoring and complex human motion recognition.