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基于超薄氧化的高性能铁电场效应晶体管用于神经形态计算

Jiawen Chen¹, Jinyu Li¹, Qimeng Zhang¹

¹School of Information Science and Technology, Fudan University, Shanghai 200433, People's Republic of China.

|May 21, 2025

概括

研究人员开发了用于内存计算 (IMC) 的氧化 (In2O3) 场效应晶体管 (FeFET),以克服人工智能硬件的局限性. 这些FeFET显示了神经形态计算应用的高性能,在图像分类中达到92.5%的准确性.

科学领域:

材料科学材料科学材料科学
计算机工程计算机工程
人工智能的人工智能

背景情况:

传统的·诺伊曼计算与人工智能的计算需求作斗争.
内存计算 (IMC) 为·诺伊曼瓶提供了一个解决方案.
场效应晶体管 (FeFET) 对IMC硬件来说是有前景的,但面临着挑战.

研究的目的:

为了演示用于神经形态计算的辅助金属氧化物半导体 (CMOS) 兼容的In2O3 FeFET阵列.
评估In2O3 FeFETs在IMC应用中的性能和潜力.

主要方法:

与CMOS工艺兼容的In2O3 FeFET阵列的制造.
FeFET性能指标的表征:开关比率,内存窗口,耐久性,保留,变化,均性和电位/低压的线性.
评估FeFET阵列在图像分类任务中的性能.

主要成果:

实现了超高的开关比率 (10^7) 和大内存窗口 (>6V).
证明了高耐力 (10^7周期),长时间保留 (>10年),低变化 (1.1%) 和高均性.
呈现出线性和对称的长期增强 (LTP) 和长期抑郁 (LTD).
在图像分类中达到92.5%的准确性.

结论:

在IMC硬件中,In2O3 FeFET显示出出色的性能特性.
开发的FeFET阵列具有构建神经形态计算系统的巨大潜力.
这项工作通过解决计算瓶,为先进的AI硬件铺平了道路.

关键词:

铁电场效应晶体管铁电场效应晶体管有氧化氧化氧化.氧化物 - - 氧化物记忆记忆记忆记忆记忆神经形态计算是一种神经形态计算.

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