Robust hybrid perovskite self-rectifying memristor for brain-inspired computing and data storage

Conventional computing architectures are not suited to meet the unique workload requirements of artificial intelligence and deep learning, which has sparked a growing interest in memory-centric computing. One primary challenge in this field is sneak path current in memory devices, which degrades data storage and reliability. Another critical issue is ensuring device performance stability over time and under varying environmental conditions. To overcome these challenges, in this work, we introduce a Dion–Jacobson perovskite-based self-rectifying memory cell that not only reduces the sneak path current but also demonstrates remarkable stability in electrical parameters. The fabricated device maintains consistent performance, including rectification ratio (∼103), on/off ratio (∼103), and set voltage (∼0.52 V), for over 200+ days within a temperature range of 25–70 °C and relative humidity conditions up to 70%RH. Importantly, our work represents an innovative step forward in the observation of self-rectification and stable performance in perovskite-based devices, showing the way for their widespread application in memory-centric computing architectures. Furthermore, to understand the electrical behavior across its different states, i.e., high resistance state and low resistance state, electrochemical impedance spectroscopy is performed, which gives insight into the individual contribution of resistance, capacitance, and inductance.