TiO活性层的多层堆叠顺序对忆阻器器件电阻开关特性的影响。

The Effect of Multi-Layer Stacking Sequence of TiO Active Layers on the Resistive-Switching Characteristics of Memristor Devices.

作者信息

Kim Minho, Yoo Kungsang, Jeon Seong-Pil, Park Sung Kyu, Kim Yong-Hoon

机构信息

School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon 16419, Korea.

School of Electrical and Electronic Engineering, Chung-Ang University, Seoul 06980, Korea.

出版信息

Micromachines (Basel). 2020 Jan 30;11(2):154. doi: 10.3390/mi11020154.

DOI:10.3390/mi11020154

PMID:32019257

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7074605/

Abstract

The oxygen vacancies in the TiO active layer play the key role in determining the electrical characteristics of TiO-based memristors such as resistive-switching behaviour. In this paper, we investigated the effect of a multi-layer stacking sequence of TiO active layers on the resistive-switching characteristics of memristor devices. In particular, the stacking sequence of the multi-layer TiO sub-layers, which have different oxygen contents, was varied. The optimal stacking sequence condition was confirmed by measuring the current-voltage characteristics, and also the retention test confirmed that the characteristics were maintained for more than 10,000 s. Finally, the simulation using the Modified National Institute of Standards and Technology handwriting recognition data set revealed that the multi-layer TiO memristors showed a learning accuracy of 89.18%, demonstrating the practical utilization of the multi-layer TiO memristors in artificial intelligence systems.

摘要

TiO 活性层中的氧空位在决定基于 TiO 的忆阻器的电学特性（如电阻开关行为）方面起着关键作用。在本文中，我们研究了 TiO 活性层的多层堆叠顺序对忆阻器器件电阻开关特性的影响。特别是，改变了具有不同氧含量的多层 TiO 子层的堆叠顺序。通过测量电流 - 电压特性确定了最佳堆叠顺序条件，并且保持测试证实这些特性在超过 10000 秒的时间内得以维持。最后，使用修改后的美国国家标准与技术研究院手写识别数据集进行的模拟表明，多层 TiO 忆阻器的学习准确率为 89.18%，证明了多层 TiO 忆阻器在人工智能系统中的实际应用。