Robust One-Dimensional Sensing Yarn for High-Performance Strain Detection in Wearables

Abstract

Yarn-based strain sensors have garnered significant attention due to their excellent flexibility, conformability, and weavability. However, manufacturing high-performance yarn strain sensors with ultradurability and high sensitivity by using simple and low-cost mass fabrication methods remains a huge challenge for wearable electronics. Herein, high-strength and microcrack-structured carbon nanotube/thermoplastic polyurethane (CNT/TPU) composite yarns were fabricated by employing simple wet spinning and prestretching techniques. Subsequently, the yarns were coated with polydimethylsiloxane (PDMS) to attain hydrophobicity and wearability. The scalable fabrication process eliminates complex synthesis steps, enabling cost-effective mass production without compromising performance. Benefiting from the ultrasensitive microcrack structure and PDMS encapsulation protection, the sensor exhibits excellent high sensitivity (gauge factor is 207.9 within 320–400% strain), wide working range (0–400%), ultralow detection limit (0.5%), fast response/recovery time (90 ms/130 ms), and long-term fatigue resistance (>20,000 cycles), enabling it to reliably and accurately distinguish intense human movements and subtle physiological signals. More importantly, with the help of machine learning algorithms, the smart gloves assembled from this yarn can accurately recognize 15 different gestures with an accuracy rate of up to 97.5%, and their overall performance remains intact even after 10 washes. Overall, the PDMS/CNTs/TPU yarns synthesized using this simple method exhibit high durability while ensuring high sensitivity and a wide strain range, providing an innovative and feasible approach for manufacturing high-quality electronic textiles.