A Consistent Model for Short-Term Instability and Long-Term Retention in Filamentary Oxide-Based Memristive Devices

Abstract

Major challenges concerning the reliability of resistive switching random access memories based on the valence change mechanism (VCM) are short-term instability and long-term retention failure of the programmed resistance state, particularly in the high resistive state. On the one hand, read noise limits the reliability of VCMs via comparatively small current jumps especially when looking at the statistics of millions of cells that are needed for industrial applications. Additionally, shaping algorithms aiming for an enlargement of the read window are observed to have no lasting effect. On the other hand, long-term retention failures limiting the lifetime of the programmed resistance states need to be overcome. The physical origin of these phenomena is still under debate and needs to be understood much better. In this work, we present a three-dimensional kinetic Monte Carlo simulation model where we implemented diffusion-limiting domains to the oxide layer of the VCM cell. We demonstrate that our model can explain both instability and retention failure consistently by the same physical processes. Further, we find that the random diffusion of oxygen vacancies plays an important role regarding the reliability of VCMs and can explain instability phenomena as the shaping failure as well as the long-term retention failure in our model. Additionally, the results of the simulations are compared with experimental data of read noise and retention investigations on ZrO2-based VCM devices.

A high throughput generative vector autoregression model for stochastic synapses

“…Efforts in this direction are motivated by advancing an understanding of physical and chemical dependencies that can in principle inform design choices on physically justified grounds. In the past decade, many different computational techniques have been employed to furnish device models, from ab initio density-functional theory (DFT), molecular dynamics (MD), kinetic Monte Carlo (KMC), finite element method (FEM), as well as ordinary differential equation (ODE) and differential algebraic equation (DAE) solvers (Ascoli et al, 2015 ; Jiang and Stewart, 2017 ; Messaris et al, 2018 ; Stewart, 2019 ; Kopperberg et al, 2021 ). The resulting models exist on a spectrum of physical abstraction, such that the cost of increasing computational speed is generally a trade-off in physical accuracy/detail (Ielmini and Milo, 2017 ).…”

Endurance of 2 Mbit Based BEOL Integrated ReRAM

“…But, in comparison with the experiment, this increase in is too low. Thus, we propose to consider and investigate additional effects like diffusion, thermodiffusion or an additional oxygen exchange at the AE in future works [20] [34] [28]. Furthermore, in our model, so far, we assumed N cell to be constant.…”

“…The present state of the cell can be easily read out non-destructively by applying a small voltage to the device. Independent of the specific application of the ReRAMs, reliability is a major issue that has to be investigated and optimized [18]± [20]. Especially, endurance meaning the ability of huge numbers of faultless consecutive switching cycles is of great interest and will therefore be in the focus of our work [21], [22].…”

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

“…Modeling the full switching behavior of these devices at multiple scales is, however, complicated by the presence of both atomic and electronic currents and by their stochastic nature. Existing multiscale models can reproduce the general trends observed in resistive switching, ,,− but face two limitations. First, they treat current with analytical trap-assisted tunneling models.…”