Artificial Neuron and Synapse Devices Based on 2D Materials,Small

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Artificial Neuron and Synapse Devices Based on 2D Materials
Small ( IF 13.0 ) Pub Date : 2021-04-04 , DOI: 10.1002/smll.202100640
Geonyeop Lee ₁ , Ji-Hwan Baek ₂ , Fan Ren ₃ , Stephen J Pearton ₄ , Gwan-Hyoung Lee _{2,

5,

6,

7} , Jihyun Kim ₁

Affiliation

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.

中文翻译：

基于二维材料的人工神经元和突触装置

模拟人脑神经功能的神经形态系统被认为是一种有吸引力的下一代计算方法，具有高能效和计算速度快的优点。在提出这些神经形态系统之后，证明人工突触和神经元可以模仿生物突触和神经元的神经功能。然而，由于神经形态功能与材料的表面特性高度相关，因此基于块状材料的神经形态器件在表面存在无法控制的缺陷以及由悬空键引起的强烈散射。因此，具有无悬键表面和优异结晶度的二维材料已成为神经形态计算硬件的有希望的候选者。首先，回顾了基本的突触行为，例如突触可塑性和学习规则，以及人工突触模拟生物突触的要求。此外，通过将基于 2D 材料的突触装置分类为人工突触的各种工作原理，总结了基于 2D 材料的突触装置的最新进展。其次，描述了人工神经元的强制行为和要求，例如全有或全无定律和不应期来模拟尖峰神经网络，并回顾了迄今为止基于二维材料的人工神经元的实现。最后，讨论了基于二维材料的神经形态装置的未来挑战和前景。通过将这些分类为人工突触的各种工作原理，总结了基于 2D 材料的突触装置的最新进展。其次，描述了人工神经元的强制行为和要求，例如全有或全无定律和不应期来模拟尖峰神经网络，并回顾了迄今为止基于二维材料的人工神经元的实现。最后，讨论了基于二维材料的神经形态装置的未来挑战和前景。通过将这些分类为人工突触的各种工作原理，总结了基于 2D 材料的突触装置的最新进展。其次，描述了人工神经元的强制行为和要求，例如全有或全无定律和不应期来模拟尖峰神经网络，并回顾了迄今为止基于二维材料的人工神经元的实现。最后，讨论了基于二维材料的神经形态装置的未来挑战和前景。

更新日期：2021-05-22

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