Emerging optoelectronic artificial synapses and memristors based on low-dimensional nanomaterials
Pengshan Xie, Dengji Li, SenPo Yip, Johnny C. Ho
Abstract
The Von Neumann architecture has been the foundation of modern computing systems. Still, its limitations in processing large amounts of data and parallel processing have become more apparent as computing requirements increase. Neuromorphic computing, inspired by the architecture of the human brain, has emerged as a promising solution for developing next-generation computing and memory devices with unprecedented computational power and significantly lower energy consumption. In particular, the development of optoelectronic artificial synaptic devices has made significant progress toward emulating the functionality of biological synapses in the brain. Among them, the potential to mimic the function of the biological eye also paves the way for advancements in robot vision and artificial intelligence. This review focuses on the emerging field of optoelectronic artificial synapses and memristors based on low-dimensional nanomaterials. The unique photoelectric properties of these materials make them ideal for use in neuromorphic and optoelectronic storage devices, with advantages including high carrier mobility, size-tunable optical properties, and low resistor–capacitor circuit delay. The working mechanisms, device structure designs, and applications of these devices are also summarized to achieve truly sense-storage-computer integrated optoelectronic artificial synapses.