Multi-filament Type RRAM by Embedding Al₂O₃ Nano-seed Layer for Realizing Neuromorphic Computing

Ying-Chun Shen^1*, Yu-Lun Chueh¹

¹Department of Materials Science and Engineering, National Tsing Hua University, Hsinchu, Taiwan

* Presenter:Ying-Chun Shen, email:kuroekyo@gmail.com

As a promising candidate for the emerging devices, 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. In this study, we embedded the nano-seed Al₂O₃ architecture in the HfO₂-based RRAM to obtain the multiple-filaments. Nano-seed Al₂O₃ architecture was fabricated by glancing angle deposition (GLAD) to confine the oxygen vacancy regions. HfO₂ layer was fabricated by atomic layer deposition (ALD) and served as the main insulator layer. With this design, the RS behaviors not only possess a multi-filament characteristic, but also presents different degrees of multi-level storage potentials. This proposed RRAM is a candidate for implementation in the neuromorphic computing system.

Keywords: RRAM, multi-filament, neuromorphic computing, nano-seed architecture, multi-level set