Multiscale Modeling of Metal-Oxide-Metal Conductive Bridging Random-Access Memory Cells: From Ab Initio to Finite-Element Calculations

Abstract

Continuum modeling is a popular, computationally efficient technique that can shed light on the resistance-switching properties of conductive bridging random-access memory (CBRAM) cells. Traditional models typically rely on many fitting parameters, but this approach uses material parameters extracted either from either ab initio or machine-learned empirical calculations. As proof of concept, the authors apply the computational framework to an SiO${}_{2}$-based CBRAM cell, and reveal the relevance of Joule heating in nanoscale devices. With the proposed multiscale methodology it is possible to explore the potential of not-yet-fabricated memory cells, and to optimize their design reliably.