Nanoionic Resistive Switching Memories: On the Physical Nature of the Dynamic Reset Process

Resistive switching memories based on the valence change mechanism have attracted great attention due to their potential use in future nanoelectronics. The working principle relies on ion migration in an oxide matrix and subsequent nanoscale redox processes leading to a resistance change. While switching from a low resistive to a high resistive state, different intermediate resistance levels can be programmed by changing the maximum applied voltage, making resistive switches highly interesting for multibit data storage and neuromorphic applications. To date, this phenomenon, which is known as gradual reset, has been reported in various experimental studies, but a comprehensive physical understanding of this key phenomenon is missing. Here, a combined experimental and numerical modeling approach is presented to address these issues. Time-resolved pulse measurements are performed to study the reset kinetics in TaOx-based nano-crossbar structures. The results are analyzed using a 2D dynamic model of nonisothermal drift–diffusion transport in the mixed electronic–ionic conducting oxide including the effect of contact potential barriers. The model accurately describes the experimental data and provides physical insights into the processes determining the gradual reset. The gradual nature can be attributed to the temperature-accelerated oxygen-vacancy motion being governed by drift and diffusion processes approaching an equilibrium situation