Electrically conductive fibers are required for various applications in modern textile technology, e.g., the manufacturing of smart textiles and fiber composite systems with textile-based sensor and actuator systems. According to the state of the art, fine copper wires, carbon rovings, or metallized filament yarns, which offer very good electrical conductivity but low mechanical elongation capabilities, are primarily used for this purpose. However, for applications requiring highly flexible textile structures, as, for example, in the case of wearable smart textiles and fiber elastomer composites, the development of electrically conductive, elastic yarns is of great importance. Therefore, highly stretchable thermoplastic polyurethane (TPU) was compounded with electrically conductive carbon nanotubes (CNTs) and subsequently melt spun. The melt spinning technology had to be modified for the processing of highly viscous TPU–CNT compounds with fill levels of up to 6 wt.% CNT. The optimal configuration was achieved at a CNT content of 5 wt.%, providing an electrical resistance of 110 Ωcm and an elongation at break of 400%.

Carbon particle-filled elastomers are a widely researched option to be used as piezoresistive strain sensors for soft robotics or human motion monitoring. Therefore, various polymers can be compounded with carbon black (CB), carbon nanotubes (CNT) or graphene. However, in many studies, the electrical resistance strain response of the carbon particle-filled elastomers is non-monotonic in dynamic evaluation scenarios. The non-monotonic material behavior is also called shoulder phenomenon or secondary peak. Until today, the underlying cause is not sufficiently well understood. In this study, several influencing test parameters on the shoulder phenomena are explored, such as strain level, strain rate and strain history. Moreover, material parameters such as CNT content and anisotropy are varied in melt-spun CNT filled thermoplastic polyurethane (TPU) filament yarns, and their non-monotonic sensor response is evaluated. Additionally, a theoretical concept for the underlying mechanism and thereupon-based model is presented. An equivalent circuit model is used, which incorporates the visco-elastic properties and the characteristic of the percolation network formed by the conductive filler material. The simulation results are in good agreement when compared to the experimental results.