Modeling resistive switching materials and devices across scales

Abstract

Resistance switching devices based on electrochemical processes have attractive significant attention in the field of nanoelectronics due to the possibility of switching in nanosecond timescales, miniaturization to tens of nanometer and multi-bit storage. Their deceptively simple structures (metal-insulator-metal stack) hide a set of complex, coupled, processes that govern their operation, from electrochemical reactions at interfaces, diffusion and aggregation of ionic species, to electron and hole trapping and Joule heating. A combination of experiments and modeling efforts are contributing to a fundamental understanding of these devices, and progress towards a predictive understanding of their operation is opening the possibility for the rational optimization. In this paper we review recent progress in modeling resistive switching devices at multiple scales; we briefly describe simulation tools appropriate at each scale and the key insight that has been derived from them. Starting with ab initio electronic structure simulations that provide an understanding of the mechanisms of operation of valence change devices pointing to the importance of the aggregation of oxygen vacancies in resistance switching and how dopants affect performance. At slightly larger scales we describe reactive molecular dynamics simulations of the operation of electrochemical metallization cells. Here the dynamical simulations provide an atomic picture of the mechanisms behind the electrochemical formation and stabilization of conductive metallic filaments that provide a low-resistance path for electronic conduction. Kinetic Monte Carlo simulations are one step higher in the multiscale ladder and enable larger scale simulations and longer times, enabling, for example, the study of variability in switching speed and resistance. Finally, we discuss physics-based simulations that accurately capture subtleties of device behavior and that can be incorporated in circuit simulations.