Scalable one-step casting of a stretchable and flexible triboelectric sensor array for multi-functional sensing

Triboelectric sensor arrays (TSAs), particularly those with stretchability and multiple variables, hold immense potential for advancing human–machine interaction and personalized healthcare. However, existing fabrication methods often suffer from complex instrumentation, material limitations, and inefficiencies that hinder rapid prototyping. In this work, a low-cost and scalable one-step casting strategy is proposed for fabricating a stretchable TSA using Ecoflex and a conductive sponge electrode. A single-electrode triboelectric nanogenerator was systematically optimized in terms of surface morphology, electrode thickness, and Ecoflex thickness, achieving an output voltage of ~ 640 V, a short-circuit current of ~ 7.5 μA, and a peak power density of 2.82 W/m², with stable performance over 12,000 cycles. Notably, the device maintained functionality under 125% strain and exhibited enhanced output at 56.25% strain, demonstrating excellent mechanical stability and robustness. Scalable TSA configurations ranging from 2 × 2 to 4 × 4 pixels were developed for multifunctional sensing applications: a 2 × 2 TSA enabled light-emitting diode (LED) control and real-time visual positioning; a 4 × 4 TSA was used as a self-powered keyboard for numerical input; and a 3 × 3 TSA integrated with a LabVIEW interface allowed touchscreen-like motion tracking. For gait monitoring, a 2 × 2 TSA-integrated insole mapped plantar pressure and achieved 99.435% user identification accuracy using a lightweight one-dimensional convolutional neural network (1D-CNN). When extended to multi-gait sensing modes (slow/normal walking, slow running), a MobileNetV4 model with channel attention achieved 96.531% accuracy across 12 identity-activity combinations. This work demonstrates a versatile and accessible platform for scalable, self-powered stretchable electronics, with broad implications for wearable systems, soft robotics, and artificial intelligence (AI)-assisted healthcare.