Two-dimensional materials-based artificial neuron devices and their working mechanism

Abstract

The rapid development of artificial intelligence and robotics has created increased demands for the efficiency and performance of computer hardware. Neuromorphic computing provides a platform to process vast datasets with low power consumption, addressing critical bottlenecks in conventional computing architectures and representing a promising approach for bridging biological systems with machines. Recent advances reported that synaptic devices based on two-dimensional (2D) layered semiconductor materials have demonstrated excellent biomimetic properties and significance for neuromorphic applications. Moreover, integrating biomimetic sensory systems with 2D materials-based synaptic devices that achieve signal sensing and spike-based information processing has received significant attention from researchers. In this review, we provide a comprehensive overview of biomimetic sensory neural systems, focusing on 2D material-based devices and their operational mechanisms. First, we provide a brief introduction to the structure of the artificial synaptic device. Then, we outline fundamental biological sensory principles and advanced artificial sensor system design, including visual, tactile, smell, taste, and auditory functions. Next, we summarize the use of bio-inspired artificial perception systems for information processing. Finally, we discuss challenges and directions for future artificial sensor systems development.