Artificial Optoelectronic Synapse Based on Purely Inorganic Polyoxometalates Crystalline Materials Enabling Reservoir Computing and Neuromorphic Vision

Abstract Polyoxometalates (POMs), a class of inorganic materials with diverse redox states, dynamic responsiveness, and multimodal stimuli sensitivity, exhibit tremendous potential in artificial synapse simulation, reservoir computing, and neuromorphic vision simulation. In this work, a series of purely inorganic POMs‐based crystalline materials are designed and synthesized, in which the bimetallic active sites, polyanions (acting as electron sponges), and high‐dimensional porous structures all contribute to the rapid transfer of photogenerated electrons. Furthermore, an advanced and convenient synapse device is fabricated to simulate neural synaptic behavior, reservoir computing, and neuromorphic vision simulation. This work systematically exhibits the unique advantages of POMs‐based materials in these domains, including their efficient dynamic memory functions, photoelectric coupling responses, and low‐energy‐consumption properties. Additionally, POMs‐based materials exhibit high sensitivity to optical signals, enabling integrated visual perception and processing in neuromorphic vision simulation through light‐induced changes in electrical properties. This study demonstrates that POMs‐based materials hold significant promise in brain‐inspired computing and artificial intelligence hardware development, providing a critical material foundation and design strategy for building next‐generation efficient and low‐energy intelligent computing systems.