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用于突触电子学和神经形态系统的二维材料。

Two-dimensional materials for synaptic electronics and neuromorphic systems.

作者信息

Wang Shuiyuan, Zhang David Wei, Zhou Peng

机构信息

State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China.

State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China.

出版信息

Sci Bull (Beijing). 2019 Aug 15;64(15):1056-1066. doi: 10.1016/j.scib.2019.01.016. Epub 2019 Jan 31.

Abstract

Synapses in biology provide a variety of functions for the neural system. Artificial synaptic electronics that mimic the biological neuron functions are basic building blocks and developing novel artificial synapses is essential for neuromorphic computation. Inspired by the unique features of biological synapses that the basic connection components of the nervous system and the parallelism, low power consumption, fault tolerance, self-learning and robustness of biological neural systems, artificial synaptic electronics and neuromorphic systems have the potential to overcome the traditional von Neumann bottleneck and create a new paradigm for dealing with complex problems such as pattern recognition, image classification, decision making and associative learning. Nowadays, two-dimensional (2D) materials have drawn great attention in simulating synaptic dynamic plasticity and neuromorphic computing with their unique properties. Here we describe the basic concepts of bio-synaptic plasticity and learning, the 2D materials library and its preparation. We review recent advances in synaptic electronics and artificial neuromorphic systems based on 2D materials and provide our perspective in utilizing 2D materials to implement synaptic electronics and neuromorphic systems in hardware.

摘要

生物学中的突触为神经系统提供了多种功能。模仿生物神经元功能的人工突触电子器件是基本构建模块,开发新型人工突触对于神经形态计算至关重要。受生物突触独特特征的启发,即神经系统的基本连接组件以及生物神经系统的并行性、低功耗、容错性、自学习和鲁棒性,人工突触电子器件和神经形态系统有潜力克服传统的冯·诺依曼瓶颈,并为处理诸如模式识别、图像分类、决策和联想学习等复杂问题创造一种新范式。如今,二维(2D)材料凭借其独特性能在模拟突触动态可塑性和神经形态计算方面备受关注。在此,我们描述生物突触可塑性和学习的基本概念、二维材料库及其制备。我们回顾基于二维材料的突触电子器件和人工神经形态系统的最新进展,并阐述我们对于利用二维材料在硬件中实现突触电子器件和神经形态系统的观点。

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