Self‐Driven Hybrid Piezomagnetic–Iontronic Mechanoreceptors for Bimodal SA/RA Perception and Tactile Synthesis

ABSTRACT Artificial tactile systems increasingly use independent transduction of slow‐adapting (SA) signals from static pressure and rapid‐adapting (RA) signals from dynamic vibrations, aiming to mimic the human skin's mechanosensory pathways for enhanced perceptual processing. Here, we present a tactile sensing system based on hybrid materials that integrate an Fe 3 O 4 ‐based piezomagnetic elastomer and a poly(vinyl chloride) (PVC)‐based iontronic gel in a unified layered architecture, enabling the orthogonal encoding of SA and RA mechanotransduction. The Fe 3 O 4 elastomer exhibits piezomagnetic coupling, yielding a magnetic flux density of ∼1.5 mT and a peak voltage modulation of ∼15 mV at 3.2 N load, while effectively capturing RA signals over a wide bandwidth up to 1 kHz. Concurrently, the iontronic PVC gel is self‐driven by the potential of the Fe 3 O 4 elastomer and delivers stable SA signal outputs with a sensitivity of 1.6/0.48 mV N − 1 (whereas the RA channel exhibits 11.4/0.75 mV N −1 ). By combining these decoupled signal modalities, we construct a haptic mapping framework that generates distinctive tactile fingerprints of object surfaces. This multimodal self‐driven sensing approach enables accurate classification of material texture, reliable slip detection, and identification of surface anomalies with different groove widths. This work offers a scalable materials strategy for intelligent robotics and human–machine interfaces.