神经形态工程学
记忆电阻器
计算机科学
材料科学
消磁场
微磁学
泄漏(经济)
人工神经网络
磁场
纳米技术
电气工程
人工智能
物理
磁化
工程类
量子力学
经济
宏观经济学
作者
Wai Lum William Mah,J. Chan,K. R. Ganesh,V. B. Naik,S. N. Piramanayagam
摘要
Recently, brain-inspired neuromorphic computing (NC) has been gaining traction as it is expected to be more power efficient and a more suitable platform for artificial intelligence. Artificial neurons and synapses are the main components of the NC architecture, and there have been many studies on artificial synapses. Experimental studies on artificial neurons that should exhibit the leaky integrate-and-fire properties are lacking due to the challenges in fabricating such a device. In this work, we have fabricated domain wall based devices consisting of (Co/Pt)n free and hard layers without interlayer exchange coupling, whereby the stray field from the hard layer triggers the automatic leakage function in the free layer. In addition, devices of smaller width were able to fully reset, showing the potential to scale down to smaller sizes. This experimental proof of concept provided evidence that the proposed neuron design has potential applications in NC. Further studies were performed via micromagnetic simulations to understand the role of the width of the device, thickness, and saturation magnetization of the hard layer.
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