Electronic synaptic characteristics and simulation application of Ag/CeO2/Pt memristor

With the development of science and technology, artificial neural networks (ANNs) have become a research spot. Furthermore, two-terminal oxide memristors with adjustable resistance have attracted extensive attention due to their simple structure, low power consumption, and easy integration, among other attractive features. Additionally, among many oxides, ceria has exhibited good performance, such as longer retention and better stability in resistive devices; however, it was currently rarely used in artificial neural synapses. In this work, a self-designed Ag/CeO2/Pt memristor was found to realize the slow transition between the high-resistance state (HRS) and low-resistance state (LRS) at a very small working voltage. It was also found to exhibit very good retention performance and cyclic characteristics. The conductivity of the device was analyzed by the current-voltage (I–V) characteristics curve. Furthermore, its artificial synaptic function was explored, and a series of neuromorphic systems simulations were carried out. Additionally, the relationships between the pulse sequence parameters and the resistance state of the device were explored, and an electrical signal simulation of Pavlov's dog experiment was designed. The findings demonstrated that the device could be used to realize the application of artificial neural synapse simulation.