Recent Progress of Optoelectronic and All-Optical Neuromorphic Devices: A Comprehensive Review of Device Structures, Materials, and Applications

Conventional von Neumann-based computing systems have inherent limitations such as high hardware complexity, relatively inferior energy efficiency, and low bandwidth. As an alternative, neuromorphic computation is emerging as a platform for next-generation artificial intelligence computing systems due to their potential advantages such as highly energy-efficient computing, robust learning, fault tolerance, and parallel processing. Moreover, to further enhance the energy efficiency and processing speed, photonic-based neuromorphic systems have gathered significant interest in the past few years. Herein, the recent progress and development of optoelectronic and all-optical neuromorphic devices is summarized, focusing on their structures, materials, and potential applications. Particularly, for optoelectronic neuromorphic devices, devices with planar and vertical structures are described along with their key strategies in materials and device structures. Next, all-optical memory and neuromorphic devices for neuromorphic computing are reviewed. Finally, the applications of optoelectronic neuromorphic devices are discussed for their potential utilization in neuromorphic computing systems.

Automated summary

Neuromorphic computation, as an alternative to conventional von Neumann-based computing systems, is emerging as a platform for next-generation artificial intelligence computing systems with potential advantages such as highly energy-efficient computing, robust learning, fault tolerance, and parallel processing. The recent progress and development of optoelectronic and all-optical neuromorphic devices are summarized, highlighting their importance in improving energy efficiency and processing speed for potential applications in neuromorphic computing systems.