High-Performance Flexible Strain Sensor Based on Thermoplastic Polyurethane Melt-Blown Nonwoven with Molybdenum Disulfide for Human Motion Monitoring

Abstract

Flexible wearable strain sensors have received great attention due to the wide applications in human motion monitoring, human–machine interfaces, and artificial intelligence robots. Thermoplastic elastic polymer films and fabrics are often used as their substrates. Thermoplastic polyurethane melt-blown nonwoven (TPU MB) can be considered as a substrate because of some advantages over these materials in terms of simple fabrication process, low price, and good breathability. Molybdenum disulfide (MoS₂), a member of transition metal dichalcogenides, is a promising candidate for next-generation flexible sensing devices due to its unique semiconductor essence and outstanding mechanical strength. Hence, we develop a high-performance flexible wearable strain sensor based on TPU MB with a microcrack structure consisting of two-dimensional (2D) MoS₂ nanosheets bridged by one-dimensional (1D) multiwalled carbon nanotubes (MWCNTs). MoS₂ and MWCNTs are anchored on the modified surface of TPU MB by polydopamine (PDA) with the assistance of simple ultrasound to obtain MoS₂/MWCNTs@TPU MB flexible strain sensors. The influence of the mass ratio of MoS₂ to MWCNTs on the sensing performances of the sensors is discussed. Due to the synergistic effect of MoS₂ with high electron mobility and MWCNTs with good conductivity, when the mass ratio of MoS₂ to MWCNTs is 1:0.9, the MoS₂/MWCNTs_0.9@TPU MB flexible strain sensor exhibits a wide sensing range from 0.5% to 300%, remarkable sensitivity (GF = 4271.9), fast response time (330 ms), and excellent durability (2600 tensile cycles). Benefiting from these superior sensing performances, this sensor can be successfully applied in monitoring large human motion (squatting, walking, and finger, elbow, and wrist bending) and subtle facial expression change (smiling, opening mouth, frowning, and raising eyebrows) as well as recognizing various vocal cord vibration modes (swallowing and pronunciation of various English words), which displays a great potential in intelligent wearable devices and soft robots.