Sensory Nervous System‐Inspired Self‐Classifying, Decoupled, Multifunctional Sensor with Resistive‐Capacitive Operation Using Silver Nanomaterials

Abstract

AbstractSelf‐classification technology has remarkable potential for autonomously discerning various stimuli without any circuit or software assistance, enabling it to realize electronic skin. In conventional self‐classification systems that rely on complex circuitry for operation, integrating the sensing and algorithm processing units inevitably leads to bulkiness in devices and bottlenecks in signal processing. In this study, the novel double‐sided structure inspired by the human nervous system is newly designed for a self‐classifying sensor (SCS) without the need for additional circuits. The sensor is layered with Ag nanocomposites that have been mechanically enhanced via interface engineering and surface treatment techniques. This structure enables the resistance‐capacitance hybrid operation, facilitating the detection and distinguishment of changes in strain, pressure, and temperature within a single device, which mimics the human sensing recognition process. Moreover, the intensity of the applied stimuli is determined by analyzing the detected signal, and precise localization of the stimuli is achieved by arraying the sensors. With its self‐classification capabilities, SCS opens promising avenues for applications in soft robotics and advanced multifunctional sensor platforms, providing a sensing system characterized by simplicity and efficiency.