铁电Hf0.5Zr0.5O2与增强的中间极化:神经形态和逻辑内存计算的平台
Heng Xiang1, Lingqi Li1, Yu-Chieh Chien1
1Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117583, Singapore.
ACS applied materials & interfaces
|May 20, 2025
概括
像Hf0.5Zr0.5O2 (HZO) 这样的铁电材料显示出用于神经形态计算和内存逻辑的增强极化. 这使得有效的突触重量调制和高精度的人工智能任务成为可能.
科学领域:
- 材料科学 材料科学 材料科学
- 固态物理 固态物理
- 计算机工程 计算机工程
背景情况:
- 铁电材料提供非挥发性,可逆极化,对于先进的计算至关重要.
- 它们的突触模拟能力是神经形态网络和逻辑内存 (LiM) 的关键.
- 利用铁电开关进行重量调节是一个尚未探索的领域.
研究的目的:
- 通过相位工程改善Hf0.5Zr0.5O2 (HZO) 中的中间和累积极化水平.
- 为了证明基于HZO的铁电场效应晶体管 (FeFETs) 用于突触重量调制.
- 在一个统一的平台上整合神经形态和LiM功能.
主要方法:
- 用Hf0.5Zr0.5O2 (HZO) 的相位工程来增强极化特性.
- 基于HZO的突触FeFET的制造和表征.
- 对于神经形态 (MNIST,时尚-MNIST) 和LiM (NOR,NAND逻辑) 任务的FeFETs的实施.
主要成果:
- 在工程HZO中获得了改善的中间和累积极化水平.
- 演示了具有广泛的突触权重 (高达8位) 和高线性度的HZO FeFET.
- 实现了高分类准确度:MNIST的98%,时尚-MNIST的88%.
- 展示了可重新配置的内存NOR/NAND逻辑和使用多门FeFET的3位逻辑状态生成.
结论:
- 工程HZO表现出增强的极化,以有效调节突触重量.
- 基于HZO的FeFET成功实现了高精度的神经形态计算和多功能LiM操作.
- 这部作品提出了一个整合学习和逻辑的统一平台,为下一代计算系统铺平了道路.
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