Analysis of the Foaming Window for Thermoplastic Polyurethane with Different Hard Segment Contents

Facile Fabrication of Highly Sensitive Thermoplastic Polyurethane Sensors with Surface- and Interface-Impregnated 3D Conductive Networks

This research aims to develop a practical, scalable, and highly conductive flexible 3D printed piezoresistive sensor with low filler content. Here, we introduced a fused deposition modeling 3D printing combined in situ spray-coating technique to develop a conductive sensor in a single shot. The graphene suspension is sprayed over each layer during the 3D printing of the sensor, which helps develop a conductive network on the surface and at the interface of the printed system. Graphene deposited on the overall surface is often affected by nanoparticle delamination and loses its function over time. To avoid this, the prepared samples are subjected to foaming. The foaming process created a low-mass-density sensor by forming a microcellular structure, and the surface-deposited graphene is embedded well on the TPU surface. The method followed in this work reveals a stable and connected conduction path with excellent electrical resistance and resistance against harsh conditions (exposure to organic solvents). Besides, the compression sensor withstood its sensitivity over a severe compressive strain of 80% and showed a GF of 1.82 and a sensitivity of 2.316 kPa^-1. The conductive network path varied based on the infill pattern, affecting its electrical sensitivity. The wiggle pattern shows good resistance; under stretching, the pattern generated a higher current and showed a delayed conductive path disconnection than other patterns. Thus, the embedded graphene/TPU conductive sensors show good stability and promising sensitivity. Furthermore, the developed sensor is used to monitor human motion and actions.