纳米粒子装饰的金属氧化物协同晶体管用于具有广泛动态范围的超低能神经形态计算
Jun-Gyu Choi1, Yoonseok Song2, Seokhyeon Baek2
1Department of Electrical and Computer Engineering, Ajou University, Suwon, 16499, Republic of Korea.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|November 30, 2025
概括
研究人员开发了纳米粒子工程电解质门的晶体管 (EGMTs) 以实现高效的神经形态计算. 这项创新显著降低了能源消耗,同时保持了高的突触忠实度,为可扩展的硬件系统铺平了道路.
科学领域:
- 材料科学 材料科学 材料科学
- 神经技术的神经技术
- 电气工程 电气工程
背景情况:
- 神经形态硬件的目标是超低能耗和高突触保真度.
- 电解质门联晶体管 (EGMT) 提供低压模拟开关,但面临的是动态范围与能源消耗的权衡.
研究的目的:
- 为了减轻EGMT的动态范围和能源消耗之间的权衡.
- 开发一个纳米粒子工程EGMT,以提高神经形态计算性能.
主要方法:
- 在印氧化通道和固体聚合物电解质的接口上嵌入了纳米粒子.
- 在设备制造中采用了溶液加工方法.
- 设备性能的特征,包括导电量状态和切换能量.
主要成果:
- 在1mV排水电压下达到50个离散导电状态.
- 显示动态范围超过78.8.
- 报告的突触切换能量为0.62 pJ/峰值,是EGMT中最低的.
结论:
- 纳米粒子工程 EGMT 有效地克服了传统 EGMT 的局限性.
- 与CMOS.相比,神经网络模拟预测显著的节能 (99.7%的训练,91.4%的推理)
- 这一进步对于实用和可扩展的神经形态硬件系统至关重要.
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