Modeling and simulation of electrochemical and surface diffusion effects in filamentary cation-based resistive memory devices

Cation -based (or electrochemical) resistive memory devices are gaining increasing interest in neuromorphic applications due to their capability to emulate the dynamic behavior of biological neurons and synapses. The utilization of such devices in neuromorphic systems necessitates a reliable physical model for the resistance switching mechanism, which is based on the formation and dissolution of a conductive filament in a thin dielectric layer, sandwiched between two metal electrodes. We propose a comprehensive model to simulate the evolution of the filament geometry under the effect of both surface diffusion caused by curvature gradient and electromechanical stress, and mass injection due to electrodeposition of cations. The model has been implemented in a C++ platform using a level -set approach based on a mixed finite element formulation, enriched by a mesh adaptation strategy to accurately and efficiently track the evolution of the filament shape. The numerical scheme is initially validated on various benchmark case studies. We then simulate the growth and self -dissolution of the filamentary geometry, incorporating an electrical model allowing a comparison with conventional cation -based memories. The simulations showcase filament formation under varying applied voltages and filament dissolution under different initial resistances.