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揭示二维忆阻器热应力下的数据存储机制

Unravelling the Data Retention Mechanisms under Thermal Stress on 2D Memristors.

作者信息

Aldana Samuel, Zhang Hongzhou

机构信息

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

School of Physics, Trinity College Dublin, Dublin D02 PN40, Ireland.

出版信息

ACS Omega. 2023 Jul 20;8(30):27543-27552. doi: 10.1021/acsomega.3c03200. eCollection 2023 Aug 1.

Abstract

Memristors based on two-dimensional (2D) materials are a rapidly growing research area due to their potential in energy-efficient in-memory processing and neuromorphic computing. However, the data retention of these emerging memristors remains sparsely investigated, despite its crucial importance to device performance and reliability. In this study, we employ kinetic Monte-Carlo simulations to investigate the data retention of a 2D planar memristor. The operation of the memristor depends on field-driven on defect migration, while thermal diffusion gradually evens the defect distribution, leading to the degradation of the high resistance state (HRS) and diminishing the ON/OFF ratio. Notably, we examine the resilience of devices based on single crystals of transition metal dichalcogenides (TMDs) in harsh environments. Specifically, our simulations show that MoS-based devices have negligible degradation after 10 years of thermal annealing at 400 K. Furthermore, the variability in data retention lifetime across different temperatures is less than 22%, indicating a relatively consistent performance over a range of thermal conditions. We also demonstrate that device miniaturization does not compromise data retention lifetime. Moreover, employing materials with higher activation energy for defect migration can significantly enhance data retention at the cost of increased switching voltage. These findings shed light on the behavior of 2D memristors and pave the way for their optimization in practical applications.

摘要

基于二维(2D)材料的忆阻器因其在节能内存处理和神经形态计算方面的潜力而成为一个快速发展的研究领域。然而,尽管这些新兴忆阻器的数据保持特性对器件性能和可靠性至关重要,但对此的研究仍然很少。在本研究中,我们采用动力学蒙特卡罗模拟来研究二维平面忆阻器的数据保持特性。忆阻器的操作取决于场驱动的缺陷迁移,而热扩散会逐渐使缺陷分布均匀,导致高阻态(HRS)退化并降低开/关比。值得注意的是,我们研究了基于过渡金属二硫属化物(TMD)单晶的器件在恶劣环境中的抗老化能力。具体而言,我们的模拟表明,基于MoS的器件在400 K下进行10年热退火后退化可忽略不计。此外,不同温度下数据保持寿命的变化小于22%,表明在一系列热条件下性能相对一致。我们还证明了器件小型化不会影响数据保持寿命。此外,使用具有更高缺陷迁移激活能的材料可以显著提高数据保持能力,但代价是开关电压增加。这些发现揭示了二维忆阻器的行为,并为其在实际应用中的优化铺平了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a57/10398860/dcec41234b70/ao3c03200_0002.jpg

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