The filament growth processes, crucial to the performance of nanodevices like resistive switching memories, have been widely investigated to realize the device optimization. With the combination of kinetic Monte Carlo (KMC) simulations and the restrictive percolation model, three different growth modes in electrochemical metallization (ECM) cells were dynamically reproduced, and an important parameter, the relative nucleation distance, was theoretically defined to measure different growth modes quantitatively; hence their transition can be well described. In our KMC simulations, the inhomogeneity of storage medium is realized through introducing evolutionary void versus non-void sites within it to mimic the real nucleation during filament growth. Finally, the renormalization group method was used in the percolation model to analytically illustrate void-concentration-dependent growth mode transition, fitting KMC simulation results quite well. Our study found that the nanostructure of the medium can dominate the filament growth dynamics, as the simulation images as well as the analytical results are consistent with experiments results. Our study spotlights a vital and intrinsic factor, void concentration (relative to defects, grains, or nanopores) of a storage medium, in inducing filament growth mode transition within ECM cells. This theoretically proves a mechanism to tune performance of ECM systems that controlling microstructures of the storage media can dominate the filament growth dynamics, indicating an accessible strategy, nanostructure processing, for device optimization of ECM memristors.
Keywords: electrochemical metallization (ECM) cells; kinetic Monte Carlo (KMC) simulations; microstructure manipulation; percolation; resistive switching.