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基于氧化铟锡/氧化锌/氧化铪/钨双层结构存储器件的神经形态计算硬件的性能增强

The Enhanced Performance of Neuromorphic Computing Hardware in an ITO/ZnO/HfO/W Bilayer-Structured Memory Device.

作者信息

Noh Minseo, Ju Dongyeol, Cho Seongjae, Kim Sungjun

机构信息

Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of Korea.

Department of Electronic and Electrical Engineering, Ewha Womans University, Seoul 03760, Republic of Korea.

出版信息

Nanomaterials (Basel). 2023 Oct 28;13(21):2856. doi: 10.3390/nano13212856.

Abstract

This study discusses the potential application of ITO/ZnO/HfO/W bilayer-structured memory devices in neuromorphic systems. These devices exhibit uniform resistive switching characteristics and demonstrate favorable endurance (>10) and stable retention (>10 s). Notably, the formation and rupture of filaments at the interface of ZnO and HfO contribute to a higher ON/OFF ratio and improve cycle uniformity compared to RRAM devices without the HfO layer. Additionally, the linearity of potentiation and depression responses validates their applicability in neural network pattern recognition, and spike-timing-dependent plasticity (STDP) behavior is observed. These findings collectively suggest that the ITO/ZnO/HfO/W structure holds the potential to be a viable memory component for integration into neuromorphic systems.

摘要

本研究探讨了ITO/ZnO/HfO/W双层结构存储器件在神经形态系统中的潜在应用。这些器件表现出均匀的电阻开关特性,并展现出良好的耐久性(>10次)和稳定的保持性(>10秒)。值得注意的是,与没有HfO层的RRAM器件相比,ZnO和HfO界面处细丝的形成和断裂有助于实现更高的开/关比,并提高循环均匀性。此外,增强和抑制响应的线性验证了它们在神经网络模式识别中的适用性,并且观察到了脉冲时间依赖可塑性(STDP)行为。这些发现共同表明,ITO/ZnO/HfO/W结构有潜力成为集成到神经形态系统中的可行存储组件。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/397e/10648049/ef5125b35b94/nanomaterials-13-02856-g001.jpg

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