@inproceedings{5ca54a745e5e4fa7901bb81ceecc34d5,
title = "Spin Orbit Torque Tunable Skyrmion Neuromorphic Devices",
abstract = "Skyrmionic devices are promising candidates for energy efficient and highly integrated data storage and computing applications, owing to their small size, topological protection, and low drive current. In this abstract we propose novel spin orbit torque (SOT) controlled skyrmion device structures and their application in neuromorphic computing. We propose a spin orbit torque-driven SOT skyrmion magnetic tunnel junction (MTJ) device showing Leaky Integrate and Fire (LIF) neuron behaviour, and a SOT-controlled MTJ synaptic device in which the skyrmion size depends on the thickness of the free layer. Furthermore, we implement the spiking neural network and artificial neural network based on these devices for MNIST data classification.",
keywords = "LIF neuron, magnetic tunnel junction, neuromorphic computing, skyrmion device, spin-orbit torque",
author = "Lone, {Aijaz H.} and Xuecui Zou and Garcia, {Glen Isaac Mac Iel} and Xiaohang Li and Hossein Fariborzi",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Emerging Electronics, ICEE 2022 ; Conference date: 11-12-2022 Through 14-12-2022",
year = "2022",
doi = "10.1109/ICEE56203.2022.10117876",
language = "English (US)",
series = "2022 IEEE International Conference on Emerging Electronics, ICEE 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 IEEE International Conference on Emerging Electronics, ICEE 2022",
address = "United States",
}