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基于钯导电细丝的高稳定性忆阻器件及其在神经形态计算中的应用

High-Stability Memristive Devices Based on Pd Conductive Filaments and Its Applications in Neuromorphic Computing.

作者信息

Wang Hong, Yan Xiaobing, Wang Shufang, Lu Nianduan

机构信息

Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, Key Laboratory of Optoelectronic Information Materials of Hebei Province, Hebei University, Baoding 071002, China.

Department of Materials Science and Engineering, National University of Singapore, 117576 Singapore.

出版信息

ACS Appl Mater Interfaces. 2021 Apr 21;13(15):17844-17851. doi: 10.1021/acsami.1c01076. Epub 2021 Apr 12.

Abstract

Memristive devices with high-density and high-speed performance have considerable potential for neuromorphic computing applications in data storage and artificial synapses. However, current memristive devices that are based on conductive filaments, such as silver, are unstable owing to the high mobility and low thermodynamic stability of the filaments. A high-quality SnSe film was deposited using the pulsed laser deposition technology, and high-performance Pd/SnSe/NSTO devices were fabricated. High-stability memristive devices can not only implement simple arithmetic function but also exhibit the centralized distribution of SET/RESET voltage and cellcell uniformity. The SET/RESET power can achieve approximately 4.1 and 61 μW power. The possibility of Pd filament formation and Pd diffusion in SnSe thin films is first confirmed by combining high-resolution transmission electron microscopy, energy-dispersive spectrometer mapping, and first principle calculation. The formation and destruction process of Pd filaments can simulate the influx and extrusion kinetics of K, Ca, or Na in biological synapses and implements considerable synaptic functions. This study thus provides a new idea for improving device performance using different filament materials, which can greatly facilitate the development of neuromorphic computing.

摘要

具有高密度和高速性能的忆阻器件在数据存储和人工突触的神经形态计算应用中具有相当大的潜力。然而,目前基于导电细丝(如银)的忆阻器件由于细丝的高迁移率和低热力学稳定性而不稳定。使用脉冲激光沉积技术沉积了高质量的SnSe薄膜,并制备了高性能的Pd/SnSe/NSTO器件。高稳定性忆阻器件不仅可以实现简单的算术功能,还表现出SET/RESET电压的集中分布和单元间的均匀性。SET/RESET功率可实现约4.1和61 μW的功率。通过结合高分辨率透射电子显微镜、能量色散光谱映射和第一性原理计算,首次证实了SnSe薄膜中Pd细丝形成和Pd扩散的可能性。Pd细丝的形成和破坏过程可以模拟生物突触中K、Ca或Na的流入和挤出动力学,并实现相当多的突触功能。因此,本研究为使用不同细丝材料提高器件性能提供了新思路,这可以极大地促进神经形态计算的发展。

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