Highly-packed Self-assembled Graphene Oxide Film-Integrated Resistive Random-Access Memory on a Silicon Substrate for Neuromorphic Application

Abstract

Abstract Resistive random-access memories (RRAMs) based on metal-oxide thin films have been studied extensively for application as synaptic devices in neuromorphic systems. The use of graphene oxide (GO) as a switching layer offers an exciting alternative to other materials such as metal-oxides. For a GO-based RRAM device to be used as a synapse device, the gradual conductance modulation is generally required to imitate adaptive synaptic weight change. However, there have been few studies demonstrating synaptic behavior with gradual memory modulation from the perspective of realizing application in neuromorphic scenarios. We present a newly developed RRAM device fabricated by implementing close-packed GO layers on a highly doped Si wafer to yield a gradual modulation of the memory as a function of the number of input pulses. By using flow-enabled self-assembly, highly uniform GO thin films can be formed on flat Si wafers in a rapid and simple process. The switching mechanism was explored through proposed scenarios reconstructing the density change of the sp2 cluster in the GO layer, resulting in a gradual conductance modulation. Finally, through a pattern-recognition simulation with a modified national institute of standards and technology database, the feasibility of using close-packed GO layers as synapse devices was successfully demonstrated.