Enhanced Switching Properties in TaOx Memristors Using Diffusion Limiting Layer for Synaptic Learning

Pei Yu Jung, Debashis Panda, Sridhar Chandrasekaran, Sailesh Rajasekaran, Tseung Yuen Tseng*

*此作品的通信作者

研究成果: Article同行評審

20 引文 斯高帕斯(Scopus)

摘要

To move towards a new generation powerful computing system, brain-inspired neuromorphic computing is expected to transform the architecture of the conventional computer, where memristors are considered to be potential solutions for synapses part. We propose and demonstrate a novel approach to achieve remarkable improvement of analog switching linearity in TaN/Ta/TaOx/Al2O3/Pt/Si memristors by varying Al2O3 layer thickness. Presence of the Al2O3 layer is confirmed from the Auger Electron Spectroscopy study. Good analog switching ratio of about 100× and superior switching uniformity are observed for the 1 nm Al2O3 based device. Multilevel capability of the memristive devices is also explored for prospective use as a synapse. More than 104 and 4×104 cycles nondegradable dc and ac endurances, respectively, alongwith 104 second retention are achieved for the optimized device. Improved linearities of 2.41 and -2.77 for potentiation and depression, respectively are obtained for such 1 nm Al2O3-based devices. The property of gradual resistance changed by pulse amplitudes confirms that the TaOx memristors can be potentially used as an electronic synapse.

原文English
文章編號8960312
頁(從 - 到)110-115
頁數6
期刊IEEE Journal of the Electron Devices Society
8
發行號1
DOIs
出版狀態Published - 15 1月 2020

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