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基于 CMOS 兼容 HfAlO 的铁电突触器件在神经形态和储层计算应用中的应用。

Ferroelectric synaptic devices based on CMOS-compatible HfAlO for neuromorphic and reservoir computing applications.

机构信息

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

出版信息

Nanoscale. 2023 May 11;15(18):8366-8376. doi: 10.1039/d3nr01294h.

DOI:10.1039/d3nr01294h
PMID:37092534
Abstract

The hafnium oxide-based ferroelectric tunnel junction (FTJ) has been actively researched because of desirable advantages such as low power and CMOS compatibility to operate as a memristor. In the case of HfAlO (HAO), the remanent polarization () value is high and the atomic radius of Al is smaller than that of Hf; therefore, ferroelectricity can be better induced without mechanical force. In this paper, we propose an FTJ using HAO as a ferroelectric layer through electrical analysis and experiments; further, we experimentally demonstrate its capability as a synaptic device. Moreover, we evaluate the maximum 2 and TER value of the device according to the difference in conditions of thickness and cell area. The optimized device conditions are analyzed, and a large value of 2 (>∼43 μC cm) is obtained. Furthermore, we show that paired-pulse facilitation, paired-pulse depression, and spike-timing-dependent plasticity can be utilized in HAO-based FTJs. In addition, this study demonstrates the use of an FTJ device as a physical reservoir to implement reservoir computing. Through a series of processes, the synaptic properties of FTJs are verified for the feasibility of their implementation as an artificial synaptic device.

摘要

基于氧化铪的铁电隧道结(FTJ)因其具有低功耗和与 CMOS 兼容的优势,可用作忆阻器,因此受到了广泛的关注。在 HfAlO(HAO)的情况下,剩余极化()值较高,并且 Al 的原子半径小于 Hf 的原子半径;因此,无需机械力就能更好地诱导铁电性。本文通过电分析和实验提出了一种使用 HAO 作为铁电层的 FTJ,并进一步实验证明了其作为突触器件的性能。此外,我们根据厚度和单元面积条件的差异,评估了器件的最大 2 和 TER 值。分析了优化后的器件条件,并获得了较大的 2(>∼43 μC cm)值。此外,我们表明,基于 HAO 的 FTJ 可用于实现成对脉冲促进、成对脉冲抑制和尖峰时间依赖可塑性。此外,本研究还展示了使用 FTJ 器件作为物理储层来实现储层计算。通过一系列过程,验证了 FTJ 的突触特性,以证明其作为人工突触器件的可行性。

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