Continuous manufacture of stretchable and integratable thermoelectric nanofiber yarn for human body energy harvesting and self-powered motion detection

Thermoelectric conversion technology provides a new method for directly collecting and converting the heat released by the human body to electrical energy, which has attracted extensive attention in the field of smart wearable electronics. However, current thermoelectric materials for wearable thermoelectric devices often face problems such as air impermeability, large volume, poor integration, and limited stretchability. Herein, an advanced fabrication approach combining coagulation-bath electrospinning and self-assembly strategies is proposed to efficiently and continuously fabricate CNT/PEDOT:PSS thermoelectric nanofiber yarns with high stretchability (similar to 350%) and seamability. During the spinning process, the nonsolvent induced phase separation and self-assembly effect result in a large amount of CNT/PEDOT:PSS loaded on each individual nanofiber. Since the thermoelectric material is loaded inside the yarn rather than simply coated on the surface, it exhibits excellent mechanical stability. In addition, based on the thermoelectric effect and seamability of the yarns, they can be integrated into gloves and masks for cold/heat source identification and human respiration monitoring in self-powered mode. Moreover, the self-powered strain sensor composed of the yarn shows corresponding thermovoltage changes for different strains, which can be used to optimize basketball players' shooting percentage. These unique features make the thermoelectric nanofiber yarn show broad prospects in smart wearable fields such as wearable generators, breathing monitoring, and exercise optimization.

Automated summary

Thermoelectric nanofiber yarns with high stretchability and seamability have the ability to convert heat energy from the human body to electrical energy. They can be used in smart wearable fields such as cold/heat source identification, breathing monitoring, and exercise optimization.