The current–voltage curves of memristors exhibit significant hysteresis effects of use for information storage and computing. Here, we provide a comparison of different devices based on MAPbI3 perovskite with different contact configurations, from a 15% efficient solar cell to a pure memristor that lacks directional photocurrent. Current–voltage curves and impedance spectroscopy give insights into the different types of hysteresis, photocapacitance, and inductance present in halide perovskites. It is shown that both halide perovskite memristors and solar cells show a large inverted hysteresis effect at the forward bias that is related to the presence of a chemical inductor component in the equivalent circuit. Based on the results, we classify the observed response according to recombination current in devices with selective contacts, to voltage-activated single-carrier device conduction in devices with symmetric contacts. These findings serve to gain an understanding of the mechanism of memristor currents in mixed ionic-electronic conductors such as halide perovskites. We establish the link in the electrical response between solar cells and memristors.

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Perovskite memristors have emerged as leading contenders in brain-inspired neuromorphic electronics. Although these devices have been shown to accurately reproduce synaptic dynamics, they pose challenges for in-depth understanding of the underlying nonlinear phenomena. Potentiation effects on the electrical conductance of memristive devices have attracted increasing attention from the emerging neuromorphic community, demanding adequate interpretation. Here, we propose a detailed interpretation of the temporal dynamics of potentiation based on nonlinear electrical circuits that can be validated by impedance spectroscopy. The fundamental observation is that the current in a capacitor decreases with time; conversely, for an inductor, it increases with time. There is no electromagnetic effect in a halide perovskite memristor, but ionic-electronic coupling creates a chemical inductor effect that lies behind the potentiation property. Therefore, we show that beyond negative transients, the accumulation of mobile ions and the eventual penetration into the charge-transport layers constitute a bioelectrical memory feature that is the key to long-term synaptic enhancement. A quantitative dynamical electrical model formed by nonlinear differential equations explains the memory-based ionic effects to inductive phenomena associated with the slow and delayed currents, invisible during the “off mode” of the presynaptic spike-based stimuli. Our work opens a new pathway for the rational development of material mimesis of neural communications across synapses, particularly the learning and memory functions in the human brain, through a Hodgkin-Huxley-style biophysical model.

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