Enhancing stability and iterative learning in neuromorphic memristor via TiN/SiOx/TiN interface engineering

Abstract

In this study, we fabricated SiO_x-based interface-type resistive random-access memory (ReRAM) devices and demonstrated their superior performance. The device was operated at voltages below 3 V with a maximum current of less than 1 mA. It exhibited an on/off ratio of approximately 10, with a set speed of 1 μs at 3 V and a reset speed of 1 μs at −4.5 V. Notably, the retention time at 85 °C reached 10⁴ s. The interface-type ReRAM displayed significant linearity owing to gradual operation, which is characteristic of long-term potentiation and long-term depression. This high linearity facilitates an impressive modified national institute of standards and technology database (MNIST) digit recognition accuracy of 92.21%. To further understand the influence of endurance on learning performance, we evaluated the impact of synaptic weight degradation by comparing both TiN/SiO_x/TiN and Pt/SiO_x/Pt devices. This approach allowed us to assess how degradation directly affects synaptic behavior and learning efficiency in neuromorphic applications. The TiN/SiO_x/TiN configuration exhibited superior endurance, as the presence of an oxygen reservoir improved synaptic performance and stability, which aligns with the gradual switching dynamics observed in our experiments and contributes to the overall device robustness and efficiency.