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An overview of the switching parameter variation of RRAM

ISSN号：1001-6538
期刊名称：Chinese Science Bulletin
时间：2014.12
页码：5324-5337
分类：TP333[自动化与计算机技术—计算机系统结构;自动化与计算机技术—计算机科学与技术] TP333.8[自动化与计算机技术—计算机系统结构;自动化与计算机技术—计算机科学与技术]
作者机构：[1]Laboratory of Nanofabrication and Novel Device Integration,Institute of Microelectronics, Chinese Academy of Sciences,Beijing 100029, China
相关基金：supported by the National Natural Science Foundation of China（61322408,61221004,61334007,61274091,61106119 and 61106082）;National Basic Research Program of China（2010CB934200 and 2011CBA00602）;National High Technology Research and Development Program of China（2011AA010401 and 2011AA010402）
相关项目：新型微电子器件集成的基础研究

作者： Sun, Haitao|Liu, Qi|Lu, Hangbing|Liu, Ming|

关键词：切换, 参数变化, 非易失性存储器, 随机存取存储器, 统计分析模型, 操作速度, 统计方法, 渗流模型, Resistive random access memory, Variation of switching parameters, Conductive filament, Percolation model

中文摘要：

抵抗随机的存取记忆(RRAM ) 被看作了下一代的 nonvolatile 记忆的最有希望的候选人之一，由于它简单设备结构，优秀可伸缩性，快操作速度和低电源消费的优点。深深地理解物理机制并且有效地控制交换参数的统计变化是促进 RRAM 进商业申请的基础。在这份报纸，基于形成的机制和传导性的细丝的破裂上的深理解，我们总结分析并且当模特儿交换象设置 / 重设电压，电流，速度或时间那样的参数的统计的方法。然后，我们分析交换参数和影响因素的分布。另外，我们也总结由基于房间的过滤模型和设置 / 重设切换动力学组成的抵抗切换的统计的分析模型。模型罐头的结果成功地解释交换 NiO- 和 HfO 的参数的试验性的分布 < 潜水艇 class= “ a-plus-plus ” > 2 台 -based RRAM 设备。模型也提供怎么改进一致性和可靠性例如上的理论指南扰乱免疫。最后，改进交换参数的一致性的一些试验性的途径被讨论。

英文摘要：

Resistive random access memory（RRAM） has been considered as one of the most promising candidates for next-generation nonvolatile memory, due to its advantages of simple device structure, excellent scalability, fast operation speed and low power consumption. Deeply understanding the physical mechanism and effectively controlling the statistical variation of switching parameters are the basis of fostering RRAM into commercial application. In this paper, based on the deep understanding on the mechanism of the formation and rupture of conductive filament, we summarize the methods of analyzing and modeling the statistics of switching parameters such as SET/RESET voltage, current, speed or time. Then, we analyze the distributions of switching parameters and the influencing factors. Additionally, we also sum up the analytical model of resistive switching statistics composed of the cell-based percolation model and SET/RESET switching dynamics. The results of the model can successfully explain the experimental distributions of switching parameters of the Ni O- and Hf O2-based RRAM devices. The model also provides theoretical guide on how to improve the uniformity and reliability such as disturb immunity. Finally, some experimental approaches to improve the uniformity of switching parameters are discussed.