In electrospinning, nanofibers are frequently produced in nonwoven web form. Their poor mechanical properties (below 100 MPa) and difficulty in tailoring the fibrous structure have restricted their applications. However, advanced materials must be highly resistant to both deformation and fracture. By combining electrospinning technology with stretching, we have overcome this disadvantage and demonstrated a polyacrylonitrile nanofiber yarn with a tensile strength of 743 ± 20 MPa. The nearly perfect uniaxial orientation of the fibrils under the stretching process is crucial for the remarkable mechanical properties of the yarn. Additionally, the nanofiber yarn was functionalized by a dip-coating process with silver nanowires (AgNWs), imparting conductive properties. This conductive, high-strength nanofiber yarn demonstrates practical applications in flexible and wearable devices. The presented strategy is versatile and can be adapted to create other high-performance nanofiber yarns, with potential uses in fields such as biomedicine and smart textiles.

High-strength nanofiber yarns exhibit pronounced nonlinear tensile responses arising from their hierarchical fibrous architecture, yet compact constitutive descriptions remain limited. Here, high-strength polyacrylonitrile nanofiber yarns were prepared by post-drawing as-spun yarns above the glass transition temperature, and their aligned, stacked morphology was confirmed by scanning electron microscopy. Monotonic tensile tests at different loading rates were used to quantify the rate-dependent stress–strain response. The tangent modulus derived from the tensile curve varied strongly with strain, confirming clear deviation from linear viscoelasticity. To capture this behavior, two effective models were established: a modified nonlinear three-element model and a structural four-element model incorporating a nonlinear elastic contribution. Closed-form stress–strain expressions were derived for constant strain-rate loading and fitted to experimental data using nonlinear regression. Both models reproduced the measured tensile curves with high accuracy over the investigated loading-rate range, with correlation coefficients close to unity and low fitting errors. The identified parameters were highly consistent between formulations, indicating functional equivalence for the present monotonic tensile dataset. These results provide a compact framework for characterizing and designing hierarchical polymer nanofiber yarns.