Within this study, the development of carbon-black (CB) doped silicone as a printable soft sensing material for integration into compliant structures is explored. Motivated by the
growing need for embedded sensing within soft robotics and biomedical devices, the research focuses on formulating printable conductive silicone recipes, characterising their mechanical and sensing behaviour, and establishing a predictive material model. Two formulations were developed to separately optimise conductivity and printability, and their performance was assessed through tensile, creep, and dynamic mechanical analysis (DMA) experiments.
The results showed that the conductive silicone exhibited greater compliance and viscoelasticity compared to its poor-conductive counterpart, with frequency-dependent hysteresis effects clearly observed. A Generalised Kelvin-Voigt model was implemented to capture the time-dependent material behaviour, yielding accurate predictions for tensile and DMA loading conditions. However, limitations in modelling the creep response and the behaviour of stiffer samples revealed the need for more complex viscoelastic or hyperelastic
formulations.