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基于离子辐照的二维 MoS 忆阻器的开关机制与优化。

On the switching mechanism and optimisation of ion irradiation enabled 2D MoS memristors.

机构信息

Centre for Research on Adaptive Nanostructures and Nanodevices (CRANN), Advanced Materials and Bioengineering Research (AMBER) Research Centers, School of Physics, Trinity College Dublin, Dublin, D02 PN40, Ireland.

出版信息

Nanoscale. 2023 Mar 30;15(13):6408-6416. doi: 10.1039/d2nr06810a.

DOI:10.1039/d2nr06810a
PMID:36929381
Abstract

Memristors are prominent passive circuit elements with promising futures for energy-efficient in-memory processing and revolutionary neuromorphic computation. State-of-the-art memristors based on two-dimensional (2D) materials exhibit enhanced tunability, scalability and electrical reliability. However, the fundamental of the switching is yet to be clarified before they can meet industrial standards in terms of endurance, variability, resistance ratio, and scalability. This new physical simulator based on the kinetic Monte Carlo (kMC) algorithm reproduces the defect migration process in 2D materials and sheds light on the operation of 2D memristors. The present work employs the simulator to study a two-dimensional 2H-MoS planar resistive switching (RS) device with an asymmetric defect concentration introduced by ion irradiation. The simulations unveil the non-filamentary RS process and propose routes to optimize the device's performance. For instance, the resistance ratio can be increased by 53% by controlling the concentration and distribution of defects, while the variability can be reduced by 55% by increasing 5-fold the device size from 10 to 50 nm. Our simulator also explains the trade-offs between the resistance ratio and variability, resistance ratio and scalability, and variability and scalability. Overall, the simulator may enable an understanding and optimization of devices to expedite cutting-edge applications.

摘要

忆阻器是一种重要的无源电路元件,在节能型内存处理和革命性的神经形态计算方面具有广阔的应用前景。基于二维 (2D) 材料的最先进忆阻器具有增强的可调谐性、可扩展性和电可靠性。然而,在它们能够满足工业标准的耐久性、可变性、电阻比和可扩展性之前,其开关的基本原理尚待阐明。这个新的基于动力学蒙特卡罗 (kMC) 算法的物理模拟器再现了二维材料中的缺陷迁移过程,并揭示了二维忆阻器的工作原理。本工作采用该模拟器研究了具有离子辐照引入的不对称缺陷浓度的二维 2H-MoS 平面电阻式开关 (RS) 器件。模拟结果揭示了非丝状 RS 过程,并提出了优化器件性能的途径。例如,通过控制缺陷的浓度和分布,可将电阻比提高 53%,通过将器件尺寸从 10nm 增加到 50nm 5 倍,可将可变性降低 55%。我们的模拟器还解释了电阻比和可变性、电阻比和可扩展性以及可变性和可扩展性之间的权衡。总的来说,该模拟器可以帮助理解和优化器件,以加速前沿应用。

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引用本文的文献

1
Identifying and understanding the nonlinear behavior of memristive devices.识别和理解忆阻器件的非线性行为。
Sci Rep. 2024 Dec 30;14(1):31633. doi: 10.1038/s41598-024-80568-y.
2
Unravelling the Data Retention Mechanisms under Thermal Stress on 2D Memristors.揭示二维忆阻器热应力下的数据存储机制
ACS Omega. 2023 Jul 20;8(30):27543-27552. doi: 10.1021/acsomega.3c03200. eCollection 2023 Aug 1.