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原子级模型揭示相变存储中电场诱导的电阻转变

An Atomistic Model of Field-Induced Resistive Switching in Valence Change Memory.

机构信息

Integrated Systems Laboratory, Department of Information Technology and Electrical Engineering, ETH Zürich, CH-8092 Zürich, Switzerland.

出版信息

ACS Nano. 2023 May 9;17(9):8281-8292. doi: 10.1021/acsnano.2c12575. Epub 2023 Mar 22.

DOI:10.1021/acsnano.2c12575
PMID:36947862
Abstract

In valence change memory (VCM) cells, the conductance of an insulating switching layer is reversibly modulated by creating and redistributing point defects under an external field. Accurately simulating the switching dynamics of these devices can be difficult due to their typically disordered atomic structures and inhomogeneous arrangements of defects. To address this, we introduce an atomistic framework for modeling VCM cells. It combines a stochastic kinetic Monte Carlo approach for atomic rearrangement with a quantum transport scheme, both parametrized at the level by using inputs from density functional theory. Each of these steps operates directly on the underlying atomic structure. The model thus directly relates the energy landscape and electronic structure of the device to its switching characteristics. We apply this model to simulate field-induced nonvolatile switching between high- and low-resistance states in a TiN/HfO/Ti/TiN stack and analyze both the kinetics and stochasticity of the conductance transitions. We also resolve the atomic nature of current flow resulting from the valence change mechanism, finding that conductive paths are formed between the undercoordinated Hf atoms neighboring oxygen vacancies. The model developed here can be applied to different material systems to evaluate their resistive switching potential, both for use as conventional memory cells and as neuromorphic computing primitives.

摘要

在变价记忆(VCM)单元中,通过在外场下创建和重新分布点缺陷,可以可逆地调制绝缘开关层的电导率。由于这些器件通常具有无序的原子结构和不均匀的缺陷排列,因此准确模拟这些器件的开关动力学可能具有挑战性。为了解决这个问题,我们引入了一种用于建模 VCM 单元的原子级框架。它结合了用于原子重排的随机动力学蒙特卡罗方法和量子输运方案,两者都通过使用密度泛函理论的输入进行参数化。这些步骤中的每一步都直接作用于基础原子结构。因此,该模型将器件的能量景观和电子结构直接与其开关特性联系起来。我们应用该模型来模拟 TiN/HfO/Ti/TiN 堆叠中高阻态和低阻态之间的场诱导非易失性开关,并分析电导率跃迁的动力学和随机性。我们还解析了由变价机制引起的电流流动的原子性质,发现相邻氧空位的低配位 Hf 原子之间形成了导电路径。这里开发的模型可以应用于不同的材料系统,以评估它们的电阻开关潜力,既可以用作传统的存储单元,也可以用作神经形态计算的基本元件。

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引用本文的文献

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Resistive Switching Devices for Neuromorphic Computing: From Foundations to Chip Level Innovations.用于神经形态计算的电阻式开关器件:从基础到芯片级创新
Nanomaterials (Basel). 2024 Mar 15;14(6):527. doi: 10.3390/nano14060527.