Artificial Neuron and Synapse Devices Based on 2D Materials

Abstract

Neuromorphic systems, which emulate neural functionalities of a human brain, are considered to be an attractive next‐generation computing approach, with advantages of high energy efficiency and fast computing speed. After these neuromorphic systems are proposed, it is demonstrated that artificial synapses and neurons can mimic neural functions of biological synapses and neurons. However, since the neuromorphic functionalities are highly related to the surface properties of materials, bulk material‐based neuromorphic devices suffer from uncontrollable defects at surfaces and strong scattering caused by dangling bonds. Therefore, 2D materials which have dangling‐bond‐free surfaces and excellent crystallinity have emerged as promising candidates for neuromorphic computing hardware. First, the fundamental synaptic behavior is reviewed, such as synaptic plasticity and learning rule, and requirements of artificial synapses to emulate biological synapses. In addition, an overview of recent advances on 2D materials‐based synaptic devices is summarized by categorizing these into various working principles of artificial synapses. Second, the compulsory behavior and requirements of artificial neurons such as the all‐or‐nothing law and refractory periods to simulate a spike neural network are described, and the implementation of 2D materials‐based artificial neurons to date is reviewed. Finally, future challenges and outlooks of 2D materials‐based neuromorphic devices are discussed.

Memristor Based on Inorganic and Organic Two-Dimensional Materials: Mechanisms, Performance, and Synaptic Applications

“…Recently, some review articles have emerged to introduce the 2D materials-based memristors. − Some reviews have focused on memory devices (including transistors and memristors) based on 2D materials . Although some reviews have focused on the recent development of memristive devices based on 2D materials and other traditional thin films. − Moreover, some reviews introduced synapse based on different memory devices . However, it is still essential to give a review focusing on memristors based on organic and inorganic 2D materials and such memristor-based synaptic applications.…”

“…35−37 Moreover, some reviews introduced synapse based on different memory devices. 38 However, it is still essential to give a review focusing on memristors based on organic and inorganic 2D materials and such memristor-based synaptic applications. Herein, we summarize the recent progress in memristors based on 2D materials, from widely studied inorganic 2D materials to recently studied organic 2D materials, as schematically shown in Figure 1.…”

2D materials and van der Waals heterojunctions for neuromorphic computing

“…The separated architecture prevents a high integration density of devices, and the data transportation in the bus leads to the high energy consumption of up to 60% of the total computing energy [9][10][11]. Moreover, the explosive growth of the data makes it further out of balance with the data bus size [3,[12][13][14][15][16][17]. In contrast with the von Neumann system, the neuromorphic computing system implements the memory and computations simultaneously in a brain-like style, which could overcome the bottleneck of the von Neumann architecture and provide a promising prospect for large data computing applications such as sound location, color and pattern recognition, and so on.…”

Two-dimensional materials for artificial synapses: toward a practical application

“…Whether the reported synaptic behaviors of those 2DM synapses meet the requirement for practical applications remains in doubt. Many excellent review papers have systematically summarized 2DM synapses from the perspectives of materials and devices [14][15][16][17][18][19][20][21][22][23][24][25]. However, a comprehensive and quantitative study that connects to system-level requirements is still lacking.…”