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

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 MoS2-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.

On the switching mechanism and optimisation of ion irradiation enabled 2D MoS2 memristors.

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-MoS2 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.