在数组配置中的三端突触晶体管的权重总和操作,使用旋转涂层添加ZrO2电解质门绝缘体
Dong-Hee Kim1, Young-Ha Kwon2, Nak-Jin Seong2
1Department of Advanced Materials Engineering for Information and Electronics, Kyung Hee University, Yongin, Gyeonggi-do 17104, Korea.
ACS applied materials & interfaces
|November 16, 2023
概括
研究人员使用杂的二氧化电解质隔离器开发了先进的人工突触. 这些设备通过模仿突触可塑性来实现高效的神经形态计算,从而实现节能模拟计算.
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.
- 电气工程 电气工程
背景情况:
- 人工突触对于硬件神经网络中节能模拟计算至关重要.
- 电解质门晶体管 (EGT) 由于电解质门绝缘体 (EGI) 的高容量,可以提供低压操作.
研究的目的:
- 通过使用In-Ga-Zn-O通道和Li-doped ZrO2 (LZO) EGI,研究基于EGT的人工突触.
- 增强短期可塑性 (STP) 和长期强化 (LTP),以改善突触功能.
主要方法:
- 制造和表征具有不同化ZrO2 (LZO) 度的EGT.
- 将兴奋剂度优化到10%以获得优异的电双层效果.
- 突触操作的演示,包括激发突触可塑性和尖峰时间依赖可塑性 (STDP) 的调制.
主要成果:
- LZO EGI表现出度依赖的特征,10%的兴奋剂被证明是最佳的.
- 通过脉冲尖峰变化成功模拟渐进的突触可塑性调制.
- 在STP (例如,配对脉冲促进) 和从STP转换为LTP的明显改善.
- 在3x3数组中实现反Hebbian的STDP和加权总和运算.
结论:
- 优化的LZO EGI显著增强了神经形态应用的人工突触功能.
- 开发的突触器件能够有效模拟复杂的神经计算.
- 这项研究为先进,节能硬件神经网络铺平了道路.
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