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Elucidating Ionic Programming Dynamics of Metal‐Oxide Electrochemical Memory for Neuromorphic Computing
Author(s) -
Jeong Yangho,
Lee Hyunjoon,
Ryu Da Gil,
Cho Seong Ho,
Lee Gawon,
Kim Sangbum,
Kim Seyoung,
Lee Yun Seog
Publication year - 2021
Publication title -
advanced electronic materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.25
H-Index - 56
ISSN - 2199-160X
DOI - 10.1002/aelm.202100185
Subject(s) - neuromorphic engineering , materials science , oxide , computer science , electrolyte , nanotechnology , artificial neural network , electrode , chemistry , artificial intelligence , metallurgy
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.