Temperature self compensation for dynamic sensitivity in 3D-printed piezoresistive sensors

Temperature variations induce nonlinear changes in the dynamic sensitivity of 3D-printed piezoresistive sensors, thereby limiting their deployment in thermally variable environments. Conventional temperature-compensation approaches rely on dedicated temperature sensors or extensive calibration matrices, which increase system complexity and reduce measurement reliability. This research investigates the hypothesis that temperature-induced changes in dynamic sensitivity in 3D-printed thermoplastic extrusion technology piezoresistive sensors are directly proportional to the changes in electrical resistance. The hypothesis was tested against twenty-four single-process 3D-printed accelerometers operating from 5 °C to 35 °C in three humidity conditions. Strong linear correlations ( R 2 > 0 . 98 ) between the relative resistance and the dynamic sensitivity changes were found. The resistance-based temperature self-compensation method does not require additional sensors. It enables accurate sensitivity prediction with errors below 5 % in normal humidity and 12 % in extreme humidity environments. This approach eliminates the need for temperature sensors while maintaining measurement accuracy, enabling the deployment of thermoplastic 3D-printed piezoresistive sensors in smart structures operating across varying environmental conditions. • Sensitivity of piezoresistive 3D-printed sensors is temperature and humidity dependent. • Linear relationship validated across temperature and humidity conditions. • Resistance measurement is proposed for temperature self compensation. • Proposed temperature compensation eliminates additional sensors while maintaining 5% accuracy.