神经形态工程学
材料科学
横杆开关
光电子学
尖峰神经网络
人工神经网络
记忆电阻器
集成电路
图层(电子)
振荡(细胞信号)
电子线路
纳米技术
计算机科学
电子工程
电气工程
人工智能
电信
生物
工程类
遗传学
作者
Jeong Woo Jeon,Byongwoo Park,Yoon Ho Jang,Soo Hyung Lee,Sangmin Jeon,Janguk Han,Seung Kyu Ryoo,Kyung Do Kim,Sung Keun Shim,Sunwoo Cheong,Wonho Choi,Gwangsik Jeon,Sung‐Jin Kim,Chanyoung Yoo,Joon‐Kyu Han,Cheol Seong Hwang
标识
DOI:10.1021/acsami.3c18625
摘要
Nanodevice oscillators (nano-oscillators) have received considerable attention to implement in neuromorphic computing as hardware because they can significantly improve the device integration density and energy efficiency compared to complementary metal oxide semiconductor circuit-based oscillators. This work demonstrates vertically stackable nano-oscillators using an ovonic threshold switch (OTS) for high-density neuromorphic hardware. A vertically stackable Ge0.6Se0.4 OTS-oscillator (VOTS-OSC) is fabricated with a vertical crossbar array structure by growing Ge0.6Se0.4 film conformally on a contact hole structure using atomic layer deposition. The VOTS-OSC can be vertically integrated onto peripheral circuits without causing thermal damage because the fabrication temperature is <400 °C. The fabricated device exhibits oscillation characteristics, which can serve as leaky integrate-and-fire neurons in spiking neural networks (SNNs) and coupled oscillators in oscillatory neural networks (ONNs). For practical applications, pattern recognition and vertex coloring are demonstrated with SNNs and ONNs, respectively, using semiempirical simulations. This structure increases the oscillator integration density significantly, enabling complex tasks with a large number of oscillators. Moreover, it can enhance the computational speed of neural networks due to its rapid switching speed.
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