Characterization and optimization of 3D-printed, flexible vibration strain sensors with triply periodic minimal surfaces

Abstract

Flexible piezoresistive strain sensors have promising applications in wearables and soft robotics. For sensing dynamic strains, such as a runner’s gait or a slipping object held by a robotic gripper, the sensor must be capable of vibration strain sensing for a range of amplitudes and frequencies. This article presents the characterization and design optimization of a flexible sensor using Schwarz P-type triply periodic minimal surface (TPMS) structures for vibration strain sensing. Sensors are fabricated using a 3D-printing process, coating a silicone rubber (SR) matrix with graphene nanoplatelets (GNP). Sensors are characterized under uniaxial compressive strain amplitudes from 0% to 10% and frequencies of 10–110 Hz. Frequency and time-domain analyses demonstrate sensor performance and explain the unique deformation mechanisms of the TPMS structure. Low sensor delays of less than 6.3 ms demonstrate its capability for high-frequency sensing. The frequency independence of the sensor is demonstrated, as the mean frequency dependence error is only ±3.89%. In addition, the TPMS sensor was parametrized, and a size optimization was performed on it using a multi-objective adaptive firefly algorithm (MOAFA). The MOAFA converged within 1618 unique function evaluations, a reduction of 85.5% compared to the entire set of feasible solutions. The optimized sensor was fabricated and characterized, displaying a reduced mean frequency dependence error of only ±2.18%.