Temperature-dependent Resistive Switching Statistics and Mechanisms in Nanoscale Graphene-SiO2-Graphene Memristors

Abstract

The development of memristors presents a transformative opportunity to revolutionize electronic devices and computing systems by enabling non-volatile memory and neuromorphic computing. Silicon oxide memristors are particularly promising due to their potential for low-cost, high-integration and compatible with existing manufacturing process. In this study, we statistically investigate the switching mechanisms of a nanoscale (sub-2nm) silicon oxide memristor at different temperature. As a unipolar memristor, average set voltage (switching from high resistive state to low resistive state) rises with temperature drop while average reset voltage (switching from low restive state to high state) drops slightly with temperature drop. Standard deviation of those values increase with temperature drops. These behaviors are analyzed based on Weibull distribution. Statistical results suggest that the set process involves the formation of Si conducting filament promoted by the diffusion of oxygen ions from oxygen vacancies, while reset process involves Joule heat driven conductive filament rupture and silicon-oxygen recombination, requiring intensified heating at higher environmental temperatures to counteract extended oxygen ion migration. Beyond general resistive switching mechanisms only involved with the formation and rupture of Si conductive filament, our insights provide a novel understanding to the stochastic nature mechanisms of the switching process at atomic level, with significant implications for future neuromorphic computing applications.