原子层沉积的铁电兰添加HfO (La:HfO) 和TaN基人工突触的突触特征
Yu-Rim Jeon1, Duho Kim2, Boncheol Ku2
1Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States.
ACS applied materials & interfaces
|December 2, 2023
概括
研究人员开发了先进的铁电突触晶体管,使用化氧化 (La:HfO2) 添加了. 这些设备显示了改进的模拟突触功能和高精度的神经网络模拟神经形态计算.
科学领域:
- 材料科学 材料科学 材料科学
- 神经科学是一个神经科学.
- 计算机工程 计算机工程
背景情况:
- 神经形态计算旨在利用电子设备模仿大脑的结构和功能.
- 基于氧化 (HfO2) 的铁电 (FE) 材料由于其非挥发性,低功耗特性,对模拟突触器件具有前景.
- 有限的研究存在于FE突触设备中,这些设备中含有稀土元素,如La,Y和Gd,接口质量对性能至关重要.
研究的目的:
- 通过研究化HfO2 (La:HfO2) 和化 (TaN) 电极来增强铁电和人工突触特性.
- 通过优化材料接口来提高残余极化 (Pr),突触导电线性和可靠性.
- 为了证明这些设备在神经形态计算应用中的潜力.
主要方法:
- 使用原子层沉积 (ALD) 制造具有 ITO/IGZO/La:HfO2/TaN 结构的铁电薄膜晶体管 (FE TFT).
- 改进的铁电性质和 doped HfO2 和 ALD TaN 薄膜的表面形态的特性.
- 评估突触行为,包括长期的强化/抑郁,线性,导电状态和可变性.
主要成果:
- 通过使用La:HfO2和ALD TaN.实现了改善的残余极化 (Pr) 和降低表面粗度.
- 证明了具有200个导电量状态的模拟突触功能,高线性 (Ap=0.97,Ad=0.86) 和高Gmax/Gmin比率 (~6.1).
- 在人工神经网络模拟中表现出低循环到循环的变化,并实现了>90%的模式识别准确性.
结论:
- 开发的基于La:HfO2的FE突触晶体管表现出卓越的模拟突触特性和可靠性.
- 该研究强调了材料兴奋剂和接口工程对于先进的神经形态器件的重要性.
- 这些发现为神经形态计算中高效和高性能的人工突触应用铺平了道路.
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