Achieving High Sensitivity and Linearity in Resistive Flexible Sensors Using FeNWs@Graphene as Conductive Fillers

There is a critical demand for flexible resistive sensors that combine high sensitivity with a wide linear range, fast response speed, and excellent long-term stability. This study presents the development of a high-performance resistive flexible sensor utilizing graphene-coated iron nanowires (Fe NWs@Graphene) as conductive fillers within a polyurethane sponge (PUS) substrate. The sensor was constructed with a sandwich-like structure, consisting of Fe NWs@Graphene-impregnated PUS as the sensing layer, encapsulated by polydimethylsiloxane (PDMS) for protection. The Fe NWs were synthesized via a chemical reduction process employing an external magnetic field. Subsequent chemical vapor deposition enabled uniform graphene coating on the surface of Fe NWs. Systematic performance assessments demonstrated that the Fe NWs@Graphene flexible sensor exhibits a gauge factor (GF) of 14.5 within a 0–100% strain range, representing a 71% improvement over previously reported Fe NW-based strain sensors, along with excellent linearity (R² = 0.994). The sensor also showed rapid response times (113 ms for loading and 97 ms for unloading) and outstanding cyclic stability over 3000 stretching cycles at 50% strain. These enhancements are attributed to the synergistic effects between Fe NWs and graphene: the graphene shell effectively protects the Fe NW core against oxidation, thereby improving stability, and facilitates efficient charge transport, while the Fe NWs serve as bridging agents that improve both mechanical integrity and electrical percolation. In addition, application tests simulating human motion detection confirmed the sensor’s ability to accurately capture muscle-induced strain signals with high repeatability. The results underscore the feasibility of Fe NWs@Graphene as conductive fillers for high-sensitivity, wide-range, and stable flexible sensors, highlighting the potential in wearable electronics and human–machine interaction systems.