Advancements in 3D printing technology facilitate the development of dual-material printed, flexible force sensors, offering enhanced performance and adaptability. Employing Fused Deposition Modeling (FDM), this study presents two geometry-fixed capacitive sensors, S1 and S2, which integrate conductive and non-conductive materials with tailored printing settings to optimize mechanical stress response. Both S1 and S2 underwent metrological characterization, including force-controlled tests ranging from 0 N to 500 N, covering a broad spectrum of applications. These sensors exhibited consistent performance across both static compression and dynamic cyclic loading-unloading tests, outperforming in medium and high force ranges. The results demonstrate remarkable sensitivity compared to the current state-of-art: S1 and S2 demonstrated relative changes in capacitance (δC/C0) reaching up to 2.41 ± 0.03 and 1.71 ± 0.12, respectively, with remarkable sensitivity values of 0.0054 N-1 and 0.0039 N-1 in high force ranges. Additionally, applicationspecific testing validated their efficacy in dynamic scenarios such as finger pressure and foot pressure monitoring, underscoring the potential of 3D-printed sensors to deliver high sensitivity and adaptability. This study establishes these sensors as cost-effective, customizable solutions, confirming their practical utility for diverse real-world applications.
Flexible Dual-Material 3D-Printed Capacitive Force Sensors: Design, Fabrication, and Metrological Characterization
Romano C.;Setola R.;Schena E.;Massaroni C.
2025-01-01
Abstract
Advancements in 3D printing technology facilitate the development of dual-material printed, flexible force sensors, offering enhanced performance and adaptability. Employing Fused Deposition Modeling (FDM), this study presents two geometry-fixed capacitive sensors, S1 and S2, which integrate conductive and non-conductive materials with tailored printing settings to optimize mechanical stress response. Both S1 and S2 underwent metrological characterization, including force-controlled tests ranging from 0 N to 500 N, covering a broad spectrum of applications. These sensors exhibited consistent performance across both static compression and dynamic cyclic loading-unloading tests, outperforming in medium and high force ranges. The results demonstrate remarkable sensitivity compared to the current state-of-art: S1 and S2 demonstrated relative changes in capacitance (δC/C0) reaching up to 2.41 ± 0.03 and 1.71 ± 0.12, respectively, with remarkable sensitivity values of 0.0054 N-1 and 0.0039 N-1 in high force ranges. Additionally, applicationspecific testing validated their efficacy in dynamic scenarios such as finger pressure and foot pressure monitoring, underscoring the potential of 3D-printed sensors to deliver high sensitivity and adaptability. This study establishes these sensors as cost-effective, customizable solutions, confirming their practical utility for diverse real-world applications.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


