A probabilistic model of resistance jumps in memristive devices

TL;DR

This paper introduces a probabilistic model for resistance jumps in memristive devices, capturing intrinsic variability and providing a new analytical framework for understanding their switching behavior.

Contribution

It presents a novel stochastic modeling approach using a state probability distribution function and integro-differential equations for resistance switching.

Findings

Derived numerical and analytical solutions for the model

Expanded modeling tools for resistance switching devices

Enabled rigorous description of physical switching behavior

Abstract

Resistance switching memory cells such as electrochemical metallization cells and valence change mechanism cells have the potential to revolutionize information processing and storage. However, the creation of deterministic resistance switching devices is a challenging problem that is still open. At present, the modeling of resistance switching cells is dominantly based on deterministic models that fail to capture the cycle-to-cycle variability intrinsic to these devices. Herewith we introduce a state probability distribution function and associated integro-differential equation to describe the switching process consisting of a set of stochastic jumps. Numerical and analytical solutions of the equation have been found in two model cases. This work expands the toolbox of models available for resistance switching cells and related devices, and enables a rigorous description of intrinsic physical behavior not available in other models.