Elucidating Ionic Programming Dynamics of Metal‐Oxide Electrochemical Memory for Neuromorphic Computing

神经形态工程学 材料科学 氧化物 计算机科学 电解质 纳米技术 人工神经网络 电极 化学 人工智能 物理化学 冶金
作者
Yangho Jeong,Hyunjoon Lee,Da Gil Ryu,Seong Ho Cho,Ga‐Won Lee,Sang‐Bum Kim,Seyoung Kim,Yun Seog Lee
出处
期刊:Advanced electronic materials [Wiley]
卷期号:7 (8) 被引量:44
标识
DOI:10.1002/aelm.202100185
摘要

Abstract Cross‐point arrays of synaptic devices have been investigated as a core platform for neuromorphic computing architectures. To achieve a significant speed boost in deep neural network computations compared to the von Neumann architecture, it is essential to develop synaptic devices with optimal performance for fully parallel vector‐matrix‐multiplication. Among various non‐volatile memory candidates, metal‐oxide based electrochemical random‐access memory (ECRAM) is considered as a promising analog synapse due to its superior switching characteristics and CMOS‐compatibility. However, the switching mechanisms of metal‐oxide ECRAM remain to be understood, impeding improvements of the synaptic characteristics and device performance. Here, ionic programming dynamics based on oxygen ion migration and associated redox‐reactions are investigated in metal‐oxide ECRAMs by considering ion transport via the electrolyte and diffusion in the channel. Additionally, the origins of update asymmetry and long‐term retention found in voltage‐pulse programming measurements are explained by non‐uniform distribution of the off‐stoichiometry in the channel layer. By exploiting the programming mechanism, ECRAMs can achieve desirable synaptic characteristics under voltage‐pulse mode. Finally, experimental and simulation studies consistently suggest that channel and electrolyte with high ionic transport properties can improve the performance of metal‐oxide ECRAMs, opening a path toward optimized synaptic device characteristics for the maximum computation performance.
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