Kim Hyeongwook, Lee Jihwan, Kim Hyun Wook, Woo Jiyong, Kim Min-Hwi, Lee Sin-Hyung
School of Electronics Engineering, and School of Electronic and Electrical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu 702-701, Republic of Korea.
School of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, Republic of Korea.
ACS Appl Mater Interfaces. 2023 Oct 24. doi: 10.1021/acsami.3c13514.
Oxide-based memristors have been demonstrated as suitable options for memory components in neuromorphic systems. In such devices, the resistive switching characteristics are caused by the formation of conductive filaments (CFs) comprising oxygen vacancies. Thus, the electrical performance is primarily governed by the CF structure. Despite various approaches for regulating the oxygen vacancy distributions in oxide memristors, controlling the CF structure without modifying the device configuration related to material compatibility is still a challenge. This study demonstrates an effective strategy for localizing CF distributions in memristors by suppressing charge injection during the formation of conducting paths. As the injected charge quantity is reduced in the electroforming process of the oxide memristor, the CF distributions become narrower, leading to more reproducible and stable resistive switching characteristics in the device. Based on these findings, a reliable hardware neural network comprising oxide memristors is constructed to recognize complex images. The developed memristor has been employed as a synaptic memory component in systems without degradation for a long time. This promising concept of oxide memristors acting as stable synaptic components holds great potential for developing practical neuromorphic systems and their expansion into artificial intelligent systems.
基于氧化物的忆阻器已被证明是神经形态系统中内存组件的合适选择。在这类器件中，电阻开关特性是由包含氧空位的导电细丝（CFs）的形成引起的。因此，电学性能主要由CF结构决定。尽管有各种方法来调节氧化物忆阻器中的氧空位分布，但在不改变与材料兼容性相关的器件配置的情况下控制CF结构仍然是一个挑战。本研究展示了一种通过在导电路径形成过程中抑制电荷注入来定位忆阻器中CF分布的有效策略。由于在氧化物忆阻器的电形成过程中注入电荷量减少，CF分布变窄，导致器件中电阻开关特性更具可重复性和稳定性。基于这些发现，构建了一个由氧化物忆阻器组成的可靠硬件神经网络来识别复杂图像。所开发的忆阻器已被用作系统中的突触记忆组件，长时间无退化。氧化物忆阻器作为稳定突触组件的这一有前景的概念在开发实用神经形态系统及其向人工智能系统的扩展方面具有巨大潜力。
