A biology-inspired model for the electrical response of solid state memristors

Abstract: Memristors stand out as promising components in the landscape of memory and computing. Memristors are generally defined by a conductance equation containing a state variable that imparts a memory effect. The current-voltage cycling causes transitions of the conductance, determined by different physical mechanisms such as the formation of conducting filaments in an insulating surrounding. Here we provide a unified description of the set and reset processes, by means of a single voltage activated relaxation time of the memory variable. This approach is based on the Hodgkin-Huxley model that is widely used to describe action potentials dynamics in neurons. We focus on halide perovskite memristors and their intersection with neuroscience-inspired computing. We show that the modelling approach adeptly replicates the experimental traits of both volatile and nonvolatile memristors. Its versatility extends across various device materials and configurations, capturing nuanced behaviors such as scan rate- and upper vertex-dependence. The model also describes well the response to sequences of voltage pulses that cause synaptic potentiation effects. This model serves as a potent tool for comprehending and probing the underlying mechanisms of memristors, by indicating the relaxation properties that control observable response, which opens the way for a detailed physical interpretation.