Progress of Nanomaterials for Neuromorphic Devices and Intelligent Vision Systems

Dear Colleagues,

Conventional CMOS vision systems are built upon a von Neumann architecture with decoupled sensing, memory, and computing functions. The massive volume of visual data captured by image sensors must be transferred over data buses to backend GPUs/CPUs for algorithmic processing, which incurs substantial power consumption and latency overheads, increases system integration complexity and manufacturing costs, and fails to meet the demand for low-power, high-real-time intelligent perception at the edge. By embedding synaptic plasticity into photosensitive devices, optoelectronic neuromorphic computing unifies optical signal sensing, feature extraction, and neural computing within a single hardware entity. It directly converts unstructured visual scenes into high-dimensional feature outputs at the sensor front end, eliminating data movement redundancy at the hardware level. This approach realizes highly efficient, intelligent visual information processing with monolithic sensing–memory–computing integration and provides a brand new technological paradigm for next-generation, low-power intelligent vision chips.

This Special Issue focuses on cutting-edge research advances and authoritative reviews in neuromorphic computing and intelligent visual processing, systematically presenting a full spectrum of innovations spanning functional materials, core devices, integration processes, and system architectures. It aims to bring together researchers across the community and to promote both fundamental breakthroughs and practical engineering deployment of optoelectronic neuromorphic technologies.

Topics of interest include, but are not limited to:

• Novel functional materials and underlying physical mechanisms;
• Synaptic devices and neuromorphic computing architectures;
• 3D heterogeneous integration technologies for optoelectronic devices;
• Sensing–memory–computing integrated intelligent visual processing systems;
• Algorithm–hardware co-design for optoelectronic neuromorphic chips;
• Nanomaterials for optoelectronic synaptic devices.

Dr. Heyi Huang
Guest Editor

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