Graphene oxide-based random access memory: from mechanism, optimization to application

According to Moore's Law's development law, traditional floating gate memory is constrained by charge tunneling, and its size is approaching the physical limit, which is insufficient to meet the requirements of large data storage. The introduction of new information storage devices may be the key to overcoming the bottleneck. Resistive random access memory (RRAM) has garnered interest due to its fast switching speed, low power consumption, and high integration density. The resistive switching (RS) behaviors can be demonstrated in many materials, including transition metal oxides, perovskite oxides and organic matter, etc. Among these materials, graphene oxide (GO) with its unique physical, chemical properties and excellent mechanical properties is attracting significant attention for use in RRAM owing to its RS operation and potential for integration with other graphene-based electronics. However, there is unacceptable variability in RS reliability, including retention and endurance, which is the key factor that affects the development of memristors. In addition, the RS mechanism of GO-based RRAM has not been systematically discussed. In this article, we discuss systematically several typical models of the switching mechanism of GO-based RRAM and a summary of methods for improving the device's RS performance. This article concludes by discussing the applications of GO-RRAM in artificial neural networks, flexible devices, and biological monitoring.