Fabrication of Amorphous SRVOX-Based Memristor for Neuromorphic Computing

Abstract

Because resistive random access memory (RRAM) has advantages, such as fast switching speed, low energy consumption, and simple device structure, it is promising device architecture for memory, artificial intelligence, and neuromorphic computing. In particular, for RRAM for use in neuromorphic applications, it must be able to mimic synaptic behavior by pulse modulation. In order to have such a characteristic, the resistance state has to be gradually changed by the stress, e.g., potentiation and depression. High linearity is required because the linearity of RRAM obtained through each resistance state is evaluated as an especially important property for artificial synaptic applications.In this work, we performed the electrical properties of sputter-deposited amorphous strontium vanadate (a-SVO) RRAM with Pt bottom electrode and Ag top electrode. Sufficient reproducibility and uniformity between devices was realized. The highest resistance ratio of ~ 103 was observed and insignificantly changed for retention testing up to 2 × 104 s. In particular, the conduction filament generated from the a-SVO RRAM was adjusted according to the regulation of voltage stress to obtain a multi-level resistance state. It was confirmed by ToF-SIMS analysis and COMSOL Multiphysics simulation that the conduction filament was formed by Ag atoms. Hopfield Neural Network simulation was conducted to verify that the performance of analog resistive switching behavior of a-SVO RRAM is suitable for neuromorphic computing. The accuracy of our simulated device was saturated to 86.8 % for 100,000 asynchronous iterations. The results imply that our a-SVO RRAM is of great potential for use in neuromorphic computing.