Controlling Multiple Filaments By Embedding Nano-Seed Layer in Resistive Random Access Memory via Glancing Angle Deposition

Abstract

Accessing data from the memory units to processing units is a main bottleneck in conventional von Neumann computing, which will give rise to latency and large energy consumption in this era of data explosion. A non-von Neumann computational approach, neuromorphic computing, has been come out recent year to speed out the data movement and alleviate the energy consumption. Resistive switching (RS)-based memristors possess several advantages such as fast switching speed, low power consumption and shrinking size that serve high potential applications in the next generation nonvolatile memory and neuromorphic computing system. However, it is difficult to realize the neuromorphic computing in filamentary resistive random access memory (RRAM). Studies have shown that multiple-filaments type RRAM is beneficial for analog switching. Herein, we developed a nano-seed functional layer embedded memory to confine the conducting filament path and achieve multiple weak filaments type RRAM, which is suggested for realizing analog behavior. Nano-seed Al2O3 architecture was fabricated by glancing angle deposition to confine the oxygen vacancy regions. HfO2 layer was fabricated by atomic layer deposition and served as the main insulator layer. The nano-seed Al2O3 layer embedded HfO2-based memory restricts several conducting filaments of 10–12 nm, which are much thinner than pure HfO2-based memory with a strong conducting filament of around 50 nm. Besides, this nano-seed Al2O3 layer embedded HfO2-based memory demonstrates multilevel cell characteristic and bi-directional analog switching behavior. This novel architecture is believed to provide a direction for realizing artificial synaptic devices in implementation of neuromorphic computing systems. Figure 1