Reliable Memristor Based on Ultrathin Native Silicon Oxide
Zelin Ma, Jun Ge, Wanjun Chen, Xucheng Cao, Shanqing Diao, Zhiyu Liu, Shusheng Pan
Abstract
Memristors based on two-dimensional (2D) materials can exhibit great scalability and ultralow power consumption, yet the structural and thickness inhomogeneity of ultrathin electrolytes lowers the production yield and reliability of devices. Here, we report that the self-limiting amorphous SiOx (∼2.7 nm) provides a perfect atomically thin electrolyte with high uniformity, featuring a record high production yield. With the guidance of physical modeling, we reveal that the atomic thickness of SiOx enables anomalous resistive switching with a transition to an analog quasi-reset mode, where the filament stability can be further enhanced using Ag–Au nanocomposite electrodes. Such a picojoule memristor shows record low switching variabilities (C2C and D2D variation down to 1.1 and 2.6%, respectively), good retention at a few microsiemens, and high conductance-updating linearity, constituting key metrics for analog neural networks. In addition, the stable high-resistance state is found to be an excellent source for true random numbers of Gaussian distribution. This work opens up opportunities in mass production of Si-compatible memristors for ultradense neuromorphic and security hardware.