2017/03/08 by Sven Dirkmann, Dirkmann, Sven, Thomas Mussenbrock +1
Engineering · Materials Science · Neuroscience · Physics and Astronomy · #Advanced Memory and Neural Computing #FOS: Physical sciences #Materials Science (cond-mat.mtrl-sci) #Mesoscale and Nanoscale Physics (cond-mat.mes-hall) #Neural dynamics and brain function #Transition Metal Oxide Nanomaterials #cond-mat.mes-hall #cond-mat.mtrl-sci
paper · pdf · doi:10.48550/arxiv.1703.02946
openalex publication_date 2017/03/08 · arxiv created 2017/06/03 · arxiv updated 2017/06/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We report on resistive switching of memristive electrochemical metallization devices using 3D kinetic Monte Carlo simulations describing the transport of ions through a solid state electrolyte of an Ag/TiOx/Pt thin layer system. The ion transport model is consistently coupled with solvers for the electric field and thermal diffusion. We show that the model is able to describe not only the formation of conducting filaments but also its dissolution. Furthermore, we calculate realistic current-voltage characteristics and resistive switching kinetics. Finally, we discuss in detail the influence of both the electric field and the local heat on the switching processes of the device.