Resistive random access memory(RRAM) has been considered as one of the most promising candidates for next-generation nonvolatile memory, due to its advantages of simple device structure, excellent scalability, fast op...Resistive random access memory(RRAM) has been considered as one of the most promising candidates for next-generation nonvolatile memory, due to its advantages of simple device structure, excellent scalability, fast operation speed and low power consumption. Deeply understanding the physical mechanism and effectively controlling the statistical variation of switching parameters are the basis of fostering RRAM into commercial application. In this paper, based on the deep understanding on the mechanism of the formation and rupture of conductive filament, we summarize the methods of analyzing and modeling the statistics of switching parameters such as SET/RESET voltage, current, speed or time. Then, we analyze the distributions of switching parameters and the influencing factors. Additionally, we also sum up the analytical model of resistive switching statistics composed of the cell-based percolation model and SET/RESET switching dynamics. The results of the model can successfully explain the experimental distributions of switching parameters of the Ni O- and Hf O2-based RRAM devices. The model also provides theoretical guide on how to improve the uniformity and reliability such as disturb immunity. Finally, some experimental approaches to improve the uniformity of switching parameters are discussed.展开更多
基金supported by the National Natural Science Foundation of China(61322408,61221004,61334007,61274091,61106119 and 61106082)National Basic Research Program of China(2010CB934200 and 2011CBA00602)National High Technology Research and Development Program of China(2011AA010401 and 2011AA010402)
文摘Resistive random access memory(RRAM) has been considered as one of the most promising candidates for next-generation nonvolatile memory, due to its advantages of simple device structure, excellent scalability, fast operation speed and low power consumption. Deeply understanding the physical mechanism and effectively controlling the statistical variation of switching parameters are the basis of fostering RRAM into commercial application. In this paper, based on the deep understanding on the mechanism of the formation and rupture of conductive filament, we summarize the methods of analyzing and modeling the statistics of switching parameters such as SET/RESET voltage, current, speed or time. Then, we analyze the distributions of switching parameters and the influencing factors. Additionally, we also sum up the analytical model of resistive switching statistics composed of the cell-based percolation model and SET/RESET switching dynamics. The results of the model can successfully explain the experimental distributions of switching parameters of the Ni O- and Hf O2-based RRAM devices. The model also provides theoretical guide on how to improve the uniformity and reliability such as disturb immunity. Finally, some experimental approaches to improve the uniformity of switching parameters are discussed.
