Electric Eels Inspired Iontronic Artificial Skin with Multimodal Perception and In‐Sensor Reservoir Computing

Abstract As the largest sensory organ, the human skin generates ionic signals in response to tactile, thermal, and electrical stimuli, which are then transmitted to neurons and processed by brain, thereby enabling sensing and memory, ultimately promoting conscious perception and decision‐making. However, existing artificial skins face significant challenges including the inability to achieve multimodal perception and memory simultaneously (i.e., tactile, thermal, and electrical stimuli), difficulty in detecting ultra‐low currents, and limitations in rich synaptic behaviors that are essential for highly efficient in‐sensor reservoir computing. Inspired by electric eels, the study here develops an artificial skin based on iontronic p‐n junctions consisting of PolyAT and PolyES bi‐layered structures. This skin features broad detection ranges for temperature (−80 to 120 °C, well beyond the reach of hydrogel counterparties), pressure (0.075 Pa to 400 kPa, among the highest sensitivities ever reported), and current (1–200 nA), meanwhile demonstrates rich synaptic behaviors and memory functions. Additionally, incorporating the iontronic skin in a robotic hand can grasp objects with different temperatures and weights on demand. Further, a fully memristive in‐sensor reservoir computing is implemented on the iontronic skin, allowing sensing, decoding, and learning via electrical stimulation, achieving 91.3% accuracy in classifying MNIST handwritten digit images.