Please use this identifier to cite or link to this item:
Title: Domain wall dynamics in (Co/Ni)n nanowire with anisotropy energy gradient for neuromorphic computing applications
Authors: Mah, William Wai Lum
Kumar, Durgesh
Jin, Tianli
Piramanayagam, S. N.
Keywords: Science::Physics
Issue Date: 2021
Source: Mah, W. W. L., Kumar, D., Jin, T. & Piramanayagam, S. N. (2021). Domain wall dynamics in (Co/Ni)n nanowire with anisotropy energy gradient for neuromorphic computing applications. Journal of Magnetism and Magnetic Materials, 537, 168131-.
Project: NRF-CRP21-2018-003
Journal: Journal of Magnetism and Magnetic Materials
Abstract: Artificial Intelligence (AI) has been gaining traction recently. However, they are executed on devices with the von Neumann architecture, requiring high power input. Consequently, brain-inspired neuromorphic computing (NC) has been gaining attention because it is expected to be more power efficient and more suitable for AI. Designing of NC circuits involves development of artificial neurons and synapses. More studies have hitherto been focused on artificial synapses instead of neurons because the latter should demonstrate leaky integrate-and-fire (LIF) properties, which is a challenge to replicate artificially. In this work, we propose a domain wall (DW) based device made from perpendicularly magnetized (Co/Ni)n nanowire (NW) with graded magnetic anisotropy and saturation magnetization. The DW is current-driven via spin-transfer-torque. Micromagnetic simulations demonstrated that the DWs in NWs with anisotropy field gradients can automatically return towards the initial position when electrical current is absent, indicative of the leakage process. The underlying physics of DW motion in such structure was studied in detail. To replicate the crystallinity of (Co/Ni)n structures, granular NWs were also defined. Depending on the grain structure of the NW, it was found that LIF properties were achieved under the conditions of steep anisotropy field gradients. Therefore, the proposed design has potential applications in neuron devices.
ISSN: 0304-8853
DOI: 10.1016/j.jmmm.2021.168131
Rights: © 2021 Elsevier B.V. All rights reserved. This paper was published in Journal of Magnetism and Magnetic Materials and is made available with permission of Elsevier B.V.
Fulltext Permission: embargo_20231108
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Journal Articles

Files in This Item:
File Description SizeFormat 
Co-Ni multilayers - revised.pdf
  Until 2023-11-08
Final submitted file2.17 MBAdobe PDFUnder embargo until Nov 08, 2023

Page view(s)

Updated on May 18, 2022

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.