Requirements and Challenges for Modelling Redox-based Memristive Devices

Abstract

Developing highly accurate and predictive models of redox-based memristive devices is highly important to enable future memory and logic design. As the switching mechanism is not known in all details yet, accurate device modeling is quite challenging. Here, we introduce six evaluation criteria for modeling filamentary switching devices based on the valence change mechanism, which is a subclass of redox-based memristive devices. The criteria include the plausibility of the simulated I-V and I-t characteristics, the nonlinearity of the switching kinetics, the feasibility of predicting complementary resistive switching correctly, the possibility of programming different resistance states, the state-dependence of the resistive switching, and the occurrence of a fading memory behavior. Four different models that have been proposed in literature are analyzed with respect to these criteria. These models are Kvatinsky's VTEAM model, the Stanford RRAM model, Strachan's TaOx memristor model and a nonlinear physics-based model proposed by our group.