Synaptic element for neuromorphic computing using a magnetic domain wall device with synthetic pinning sites
The ability to make devices that mimic the human brain has been a subject of great interest in scientific research in recent years. Current artificial intelligence algorithms are primarily executed on the von Neumann hardware. This causes a bottleneck in processing speeds and is not energy efficient...
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sg-ntu-dr.10356-1419862023-02-28T19:47:01Z Synaptic element for neuromorphic computing using a magnetic domain wall device with synthetic pinning sites Jin, Tianli Gan, Weiliang Tan, Funan Sernicola, Nicolo Roberto Lew, Wen Siang Piramanayagam, S. N. School of Physical and Mathematical Sciences Science::Physics Neuromorphic Computing Domain Wall Device The ability to make devices that mimic the human brain has been a subject of great interest in scientific research in recent years. Current artificial intelligence algorithms are primarily executed on the von Neumann hardware. This causes a bottleneck in processing speeds and is not energy efficient. In this work, we have demonstrated a synaptic element based on a magnetic domain wall device. The domain wall motion was controlled with the use of synthetic pinning sites, which were introduced by boron (B+) ion-implantation for local modification of the magnetic properties. The magnetization switching process of a Co/Pd multilayer structure with perpendicular magnetic anisotropy was observed by using MagVision Kerr microscopy system. The B+ implantation depth was controlled by varying the thickness of a Ta overcoat layer. The Kerr microscopy results correlate with the electrical measurements of the wire which show multiple resistive states. The control of the domain wall motion with the synthetic pinning sites is demonstrated to be a reliable technique for neuromorphic applications. NRF (Natl Research Foundation, S’pore) MOE (Min. of Education, S’pore) Accepted version 2020-06-12T13:11:42Z 2020-06-12T13:11:42Z 2019 Journal Article Jin, T., Gan, W., Tan, F., Sernicola, N. R., Lew, W. S., & Piramanayagam, S. N. (2019). Synaptic element for neuromorphic computing using a magnetic domain wall device with synthetic pinning sites. Journal of Physics D: Applied Physics, 52(44), 445001-. doi:10.1088/1361-6463/ab35b7 0022-3727 https://hdl.handle.net/10356/141986 10.1088/1361-6463/ab35b7 44 52 en Journal of Physics D: Applied Physics © 2019 IOP Publishing Ltd. All rights reserved. This is an author-created, un-copyedited version of an article accepted for publication in Journal of Physics D: Applied Physics. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The definitive publisher authenticated version is available online at https://doi.org/10.1088/1361-6463/ab35b7 application/pdf |
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Science::Physics Neuromorphic Computing Domain Wall Device Jin, Tianli Gan, Weiliang Tan, Funan Sernicola, Nicolo Roberto Lew, Wen Siang Piramanayagam, S. N. Synaptic element for neuromorphic computing using a magnetic domain wall device with synthetic pinning sites |
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The ability to make devices that mimic the human brain has been a subject of great interest in scientific research in recent years. Current artificial intelligence algorithms are primarily executed on the von Neumann hardware. This causes a bottleneck in processing speeds and is not energy efficient. In this work, we have demonstrated a synaptic element based on a magnetic domain wall device. The domain wall motion was controlled with the use of synthetic pinning sites, which were introduced by boron (B+) ion-implantation for local modification of the magnetic properties. The magnetization switching process of a Co/Pd multilayer structure with perpendicular magnetic anisotropy was observed by using MagVision Kerr microscopy system. The B+ implantation depth was controlled by varying the thickness of a Ta overcoat layer. The Kerr microscopy results correlate with the electrical measurements of the wire which show multiple resistive states. The control of the domain wall motion with the synthetic pinning sites is demonstrated to be a reliable technique for neuromorphic applications. |
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School of Physical and Mathematical Sciences |
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School of Physical and Mathematical Sciences Jin, Tianli Gan, Weiliang Tan, Funan Sernicola, Nicolo Roberto Lew, Wen Siang Piramanayagam, S. N. |
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Article |
author |
Jin, Tianli Gan, Weiliang Tan, Funan Sernicola, Nicolo Roberto Lew, Wen Siang Piramanayagam, S. N. |
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Jin, Tianli |
title |
Synaptic element for neuromorphic computing using a magnetic domain wall device with synthetic pinning sites |
title_short |
Synaptic element for neuromorphic computing using a magnetic domain wall device with synthetic pinning sites |
title_full |
Synaptic element for neuromorphic computing using a magnetic domain wall device with synthetic pinning sites |
title_fullStr |
Synaptic element for neuromorphic computing using a magnetic domain wall device with synthetic pinning sites |
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Synaptic element for neuromorphic computing using a magnetic domain wall device with synthetic pinning sites |
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synaptic element for neuromorphic computing using a magnetic domain wall device with synthetic pinning sites |
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2020 |
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https://hdl.handle.net/10356/141986 |
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