Comparative characterization of FDM structures with electrically-conductive sensing elements under static, dynamic and thermal loads

Fused filament fabrication (FFF), or fused deposition modeling (FDM), is one of the most widely accessible additive manufacturing (AM) processes. Recent advancements in this technology have expanded its material portfolio to include conductive composites with electromechanical properties, enabling new applications. The thermal melting of the filament, required for material extrusion, introduces variability in the final component properties, which are difficult to predict due to the influence of several process-related parameters. In particular, for applications where mechanical and electrical properties are critical, it is essential to optimize the process to control both the mechanical performance and electrical conductivity of the material in static and dynamic conditions. Post-process thermal treatments can significantly alter these electromechanical transduction properties. In this study, we investigate the static, dynamic, and thermal behavior of two composite filaments. The microstructure of the feedstock materials was analyzed using scanning electron microscopy (SEM) to establish a correlation between material composition and component behavior. The results demonstrate that the inclusion of specific fillers, such as black carbon, enhances electrical resistance and improves electromechanical stability under static and dynamic conditions. In contrast, graphene additives increase electromechanical sensitivity but result in a degradation of electrical properties during thermal treatment.