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基于垂直硅纳米线的具有兴奋、抑制和髓鞘化功能的单晶体管神经元,用于可扩展的神经形态硬件。

A Vertical Silicon Nanowire Based Single Transistor Neuron with Excitatory, Inhibitory, and Myelination Functions for Highly Scalable Neuromorphic Hardware.

机构信息

School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Daejeon, Yuseong-gu, 34141, Republic of Korea.

出版信息

Small. 2021 Dec;17(49):e2103775. doi: 10.1002/smll.202103775. Epub 2021 Oct 4.

DOI:10.1002/smll.202103775
PMID:34605173
Abstract

A single transistor neuron (1T-neuron) is demonstrated by using a vertically protruded nanowire from an 8 in. silicon (Si) wafer. The 1T-neuron adopts a gate-all-around structure to completely surround the Si nanowire (Si-NW) to make a floating body and allow aggressive downscaling. The Si-NW is composed of an n drain at the top, n source at the bottom, and p-type floating body at the middle, which are self-aligned vertically. Thus, it occupies a small footprint area. The gate controls an excitatory/inhibitory function. In addition, myelination of a biological neuron that changes membrane capacitance is mimicked by an inherently asymmetric source/drain structure. Two spiking frequencies at the same input current are controlled by whether the neuron is myelinated or unmyelinated. Using the vertical 1T-neuron, pattern recognition is demonstrated with both measurements and semiempirical circuit simulations. Furthermore, handwritten numbers in the MNIST database are recognized with accuracy of 93% by software-based simulations. Applicability of the vertical 1T-neuron to various neural networks is verified, including a single-layer perceptron, multilayer perceptron, and spiking neural network.

摘要

一种单晶体管神经元(1T-神经元)是通过使用从 8 英寸硅(Si)晶圆垂直突出的纳米线来实现的。1T-神经元采用全环绕栅极结构,完全环绕 Si 纳米线(Si-NW)以形成浮置体,并允许进行激进的缩小。Si-NW 由顶部的 n 漏极、底部的 n 源极和中间的 p 型浮置体组成,它们垂直自对准。因此,它占用的面积很小。栅极控制兴奋/抑制功能。此外,通过固有的不对称源/漏极结构模拟了生物神经元的髓鞘化,这会改变膜电容。通过控制神经元是否髓鞘化或未髓鞘化,可以控制相同输入电流下的两种尖峰频率。使用垂直 1T-神经元,通过测量和半经验电路模拟进行了模式识别。此外,通过软件模拟,手写数字在 MNIST 数据库中的识别准确率达到 93%。验证了垂直 1T-神经元在各种神经网络中的适用性,包括单层感知器、多层感知器和尖峰神经网络。

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引用本文的文献

1
Mimicking the retinal neuron functions by a photoresponsive single transistor with a double gate.通过具有双栅极的光响应单晶体管模拟视网膜神经元功能。
Biophys J. 2024 Jul 2;123(13):1804-1814. doi: 10.1016/j.bpj.2024.05.023. Epub 2024 May 23.
2
A Vertical Single Transistor Neuron with Core-Shell Dual-Gate for Excitatory-Inhibitory Function and Tunable Firing Threshold Voltage.一种具有核壳双栅的垂直单晶体管神经元,用于兴奋-抑制功能和可调触发阈值电压。
Micromachines (Basel). 2022 Oct 14;13(10):1740. doi: 10.3390/mi13101740.