Flexible Monte-Carlo approach to simulate electroforming and resistive switching in filamentary metal-oxide memristive devices

Abstract

An original approach has been presented to model the regularities and parameters of resistive switching based on the kinetic Monte Carlo (kMС) 3D simulation of stochastic migration of oxygen vacancies/ions in metal-oxide memristive devices promising for applications in emerging nonvolatile memory, in-memory and neuromorphic computing systems. The efficiency and flexibility of the approach is demonstrated by the examples of experimentally realized Au/oxide/TiN memristive device structures, in which yttria-stabilized zirconia (ZrO2(Y)) polycrystalline films and amorphous SiOx columnar films obtained by magnetron sputtering are used as the switching oxide material. The proposed approach combines the universal kMС framework for ion migration and relatively simple physics-based methods for taking into account additional factors related to the structure and morphology of specific oxide material, interface phenomena and energetics of electronic processes, and therefore does not require time-consuming calculations and is not critical to the computing power.

Influence of the active TaN/ZrO x /Ni memristor layer oxygen content on forming and resistive switching behavior

“…For simulation of these processes, the Monte Carlo method is often utilized, with oxygen vacancies redistribution acting as a primary driving force. Good agreement with the experimental data has been reached by this approach [8][9][10]. However, it is not infrequent that in such studies the time period corresponding to these processes is either not mentioned, or turns out to be several orders of magnitude greater than that in the real memristors, for which the resistive RS occurs in a few nanoseconds or even fractions of a nanosecond [1].…”

Multiscale Modeling of Ion Dynamics in Memristive Elements

“…Models of various complexity levels are presented in other studies. [25][26][27][28][29][30][31] The most comprehensive approach suggests direct simulation of the processes of oxygen ion generation/ recombination, ion, and electron transport in the memristor layer. As a rule, Monte Carlo simulators are used to describe the dynamics of ions in the system.…”

“…As a rule, Monte Carlo simulators are used to describe the dynamics of ions in the system. [29][30][31] This approach is associated with high computational costs; however, it allows one to reproduce a detailed picture of the filamentous formations. In this article, we propose a multiscale computational scheme for an ion dynamics simulation that allows modeling based on primary information-data on the chemical composition of the material and its crystal structure.…”

Accounting for Heat Release in Small Volumes of Matter on the Example of the Growth of ZnO Microrods: Search for a Modeling Technique

“…Ярким примером этого является запутанный вопрос о температуре области филамента при протекании тока в мемристивном элементе [2][3][4]. Ниже на примере роста микростержней ZnO [5][6][7] с переходами V → S (Vapor → Solid) или V → L → S (Vapor → Liquid → Solid) рассмотрим возникающие противоречия при лобовом применении для малых объемов вещества классических методов: закона Фурье и уравнения теплопроводности.…”