Synaptic plasticity investigation in permalloy based channel material for neuromorphic computing
Artificial synaptic devices capable of synchronized storing and processing of information are the critical building blocks of neuromorphic computing systems for the low-power implementation of artificial intelligence. Compared to the diverse synaptic device structures, the emerging electrolyte-gated...
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sg-ntu-dr.10356-1672312023-05-22T15:38:48Z Synaptic plasticity investigation in permalloy based channel material for neuromorphic computing Monalisha, P. Li, Shengyao Jin, Tianli Kumar, P. S. Anil Piramanayagam, S. N. School of Physical and Mathematical Sciences Division of Physics and Applied Physics Science::Physics::Atomic physics::Solid state physics Artificial Intelligence Neuromorphic Computing Electrolyte Gating Artificial synaptic devices capable of synchronized storing and processing of information are the critical building blocks of neuromorphic computing systems for the low-power implementation of artificial intelligence. Compared to the diverse synaptic device structures, the emerging electrolyte-gated synaptic transistors are promising for mimicking biological synapses owing to their analogous working mode. Despite the remarkable progress in electrolyte-gated synaptic transistors, the study of metallic channel-based synaptic devices remains vastly unexplored. Here, we report a three-terminal electrolyte-gated artificial synapse based on metallic permalloy as the active layer. Gating controlled, non-volatile, rewritable, and distinct multilevel conductance states have been achieved for analog computing. Representative synaptic behaviors such as excitatory postsynaptic conductance (EPSC), paired-pulse facilitation (PPF), spike amplitude-dependent plasticity (SADP), spike duration-dependent plasticity (SDDP), and long-term potentiation/depression (LTP/D) have been successfully simulated in the synaptic device. Furthermore, switching from short-term to long-term memory regimes has been demonstrated through repeated training. Benefitting from the short-term facilitation, the synaptic device can also act as a high-pass temporal filter for selective communication. This research highlights the great potential of metallic channel-based synaptic devices for future neuromorphic systems and augments the diversity of synaptic devices. Ministry of Education (MOE) National Research Foundation (NRF) Submitted/Accepted version The authors acknowledge the support from the CRP Grant NRF-CRP21-2018-0003 of the National Research Foundation (NRF), Singapore. SNP acknowledges the partial support from the Tier 2 grant MOE2019-T2-1-117 of the Ministry of Education (MOE) Singapore. PSAK acknowledges support from the Ministry of Education (MoE), India. 2023-05-18T02:18:29Z 2023-05-18T02:18:29Z 2023 Journal Article Monalisha, P., Li, S., Jin, T., Kumar, P. S. A. & Piramanayagam, S. N. (2023). Synaptic plasticity investigation in permalloy based channel material for neuromorphic computing. Journal of Physics D: Applied Physics, 56(1), 015302-. https://dx.doi.org/10.1088/1361-6463/ac9b6b 0022-3727 https://hdl.handle.net/10356/167231 10.1088/1361-6463/ac9b6b 1 56 015302 en NRF-CRP21-2018-0003 MOE2019-T2-1-117 Journal of Physics D: Applied Physics © 2022 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/ac9b6b. application/pdf |
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Science::Physics::Atomic physics::Solid state physics Artificial Intelligence Neuromorphic Computing Electrolyte Gating Monalisha, P. Li, Shengyao Jin, Tianli Kumar, P. S. Anil Piramanayagam, S. N. Synaptic plasticity investigation in permalloy based channel material for neuromorphic computing |
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Artificial synaptic devices capable of synchronized storing and processing of information are the critical building blocks of neuromorphic computing systems for the low-power implementation of artificial intelligence. Compared to the diverse synaptic device structures, the emerging electrolyte-gated synaptic transistors are promising for mimicking biological synapses owing to their analogous working mode. Despite the remarkable progress in electrolyte-gated synaptic transistors, the study of metallic channel-based synaptic devices remains vastly unexplored. Here, we report a three-terminal electrolyte-gated artificial synapse based on metallic permalloy as the active layer. Gating controlled, non-volatile, rewritable, and distinct multilevel conductance states have been achieved for analog computing. Representative synaptic behaviors such as excitatory postsynaptic conductance (EPSC), paired-pulse facilitation (PPF), spike amplitude-dependent plasticity (SADP), spike duration-dependent plasticity (SDDP), and long-term potentiation/depression (LTP/D) have been successfully simulated in the synaptic device. Furthermore, switching from short-term to long-term memory regimes has been demonstrated through repeated training. Benefitting from the short-term facilitation, the synaptic device can also act as a high-pass temporal filter for selective communication. This research highlights the great potential of metallic channel-based synaptic devices for future neuromorphic systems and augments the diversity of synaptic devices. |
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School of Physical and Mathematical Sciences |
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School of Physical and Mathematical Sciences Monalisha, P. Li, Shengyao Jin, Tianli Kumar, P. S. Anil Piramanayagam, S. N. |
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Article |
author |
Monalisha, P. Li, Shengyao Jin, Tianli Kumar, P. S. Anil Piramanayagam, S. N. |
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Monalisha, P. |
title |
Synaptic plasticity investigation in permalloy based channel material for neuromorphic computing |
title_short |
Synaptic plasticity investigation in permalloy based channel material for neuromorphic computing |
title_full |
Synaptic plasticity investigation in permalloy based channel material for neuromorphic computing |
title_fullStr |
Synaptic plasticity investigation in permalloy based channel material for neuromorphic computing |
title_full_unstemmed |
Synaptic plasticity investigation in permalloy based channel material for neuromorphic computing |
title_sort |
synaptic plasticity investigation in permalloy based channel material for neuromorphic computing |
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2023 |
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https://hdl.handle.net/10356/167231 |
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1772825418264477696 |