Domain wall dynamics in (Co/Ni)n nanowire with anisotropy energy gradient for neuromorphic computing applications
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...
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| Format: | Journal Article |
| Language: | English |
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2022
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| Online Access: | https://hdl.handle.net/10356/156431 |
| _version_ | 1811677606837223424 |
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| author | Mah, William Wai Lum Kumar, Durgesh Jin, Tianli Piramanayagam, S. N. |
| author2 | School of Physical and Mathematical Sciences |
| author_facet | School of Physical and Mathematical Sciences Mah, William Wai Lum Kumar, Durgesh Jin, Tianli Piramanayagam, S. N. |
| author_sort | Mah, William Wai Lum |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T02:40:03Z |
| format | Journal Article |
| id | ntu-10356/156431 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:40:03Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1564312023-02-28T20:02:26Z Domain wall dynamics in (Co/Ni)n nanowire with anisotropy energy gradient for neuromorphic computing applications Mah, William Wai Lum Kumar, Durgesh Jin, Tianli Piramanayagam, S. N. School of Physical and Mathematical Sciences Science::Physics Spintronics Neuromorphic Computing Synthetic Neurons 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. National Research Foundation (NRF) Submitted/Accepted version The authors acknowledge National Supercomputing Centre Singapore (NSCC) for providing computing facilities and the funding from National Research Foundation (NRF) Singapore for the grants NRF-CRP21-2018-003 and NRF2015-IIP003-001. 2022-04-20T05:43:56Z 2022-04-20T05:43:56Z 2021 Journal Article 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-. https://dx.doi.org/10.1016/j.jmmm.2021.168131 0304-8853 https://hdl.handle.net/10356/156431 10.1016/j.jmmm.2021.168131 537 168131 en NRF-CRP21-2018-003 NRF2015-IIP003-001 Journal of Magnetism and Magnetic Materials © 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. application/pdf |
| spellingShingle | Science::Physics Spintronics Neuromorphic Computing Synthetic Neurons Mah, William Wai Lum Kumar, Durgesh Jin, Tianli Piramanayagam, S. N. Domain wall dynamics in (Co/Ni)n nanowire with anisotropy energy gradient for neuromorphic computing applications |
| title | Domain wall dynamics in (Co/Ni)n nanowire with anisotropy energy gradient for neuromorphic computing applications |
| title_full | Domain wall dynamics in (Co/Ni)n nanowire with anisotropy energy gradient for neuromorphic computing applications |
| title_fullStr | Domain wall dynamics in (Co/Ni)n nanowire with anisotropy energy gradient for neuromorphic computing applications |
| title_full_unstemmed | Domain wall dynamics in (Co/Ni)n nanowire with anisotropy energy gradient for neuromorphic computing applications |
| title_short | Domain wall dynamics in (Co/Ni)n nanowire with anisotropy energy gradient for neuromorphic computing applications |
| title_sort | domain wall dynamics in co ni n nanowire with anisotropy energy gradient for neuromorphic computing applications |
| topic | Science::Physics Spintronics Neuromorphic Computing Synthetic Neurons |
| url | https://hdl.handle.net/10356/156431 |
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