The Research Of Black Phosphorus Based Memristor With High Performance And Application

The micro and high density integration of semiconductor technology has approached the limit,hopes are high for the new generation of memory.Memristor has attracted extensive attention due to its large storage capacity,high processing efficiency and many significant advantages of multi-functional integration in a single device.It is usually difficult to achieve the balance of device size scaling and low power consumption in the traditional oxide materials based memristors.The scaling down of switching media only acquire lower operating voltage but encounters high leakage current in the device,resulting in high power consumption of the chips.Two-dimensional(2D)materials promise the ultimate device scaling down to atomic layer thickness.To combine the advances of oxide materials with 2D materials,herein,black phosphorus(BP)and its self-assembly oxide(PO_x/BP)memristors are constructed,which exhibit reproducible and reliable switching characteristics.The main work can be summarized as follows:(1)The classical structure of sandwich is adopted in the structure design of the device.Ultraviolet light is introduced in the atmosphere conditions to produce ozone.Thus,the self-assembly PO_xlayer is obtained onto the BP surface,where the oxidation levels of the BP flakes can be modulated by adjusting the treatment durations.the memristors exhibit switching characteristics with on/off ratio>10~7and data retention>10~4s.(2)A resistance conversion model was built based on oxygen vacancy migration to form conductive filaments,which was proved by light and low temperature experiments.And through the following aspects to prove:1.Explore the relationship between ultraviolet light,low temperature with device characteristics.2.The memristor performance was investigated by using graphene with atomic layer thickness instead of metal electrode.(3)Owing to high reliability of these devices,the basic"AND"and"OR"gates have been constructed.Moreover,on the basis of the symmetry and linearity of conductance in the devices,the neural network simulation for the supervised learning presents an online learning accuracy of 91.4%.Therefore,the PO_x/BP memristors open an avenue for future low power integrated electronic equipment.