Synaptic devices towards neuromorphic electronics

New research has introduced neuromorphic systems that use artificial synapses as devices to carry out the development of platforms for interfacing biological tissues. These cutting-edge transistor-based synaptic systems offer a range of advantages including increased stability, controllable paramete...

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Main Author: Datta, Indira
Other Authors: Wang Xiao, Renshaw
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
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Online Access:https://hdl.handle.net/10356/175688
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1756882024-05-06T15:37:33Z Synaptic devices towards neuromorphic electronics Datta, Indira Wang Xiao, Renshaw School of Physical and Mathematical Sciences renshaw@ntu.edu.sg Physics Artificial synapses Electrolyte gating New research has introduced neuromorphic systems that use artificial synapses as devices to carry out the development of platforms for interfacing biological tissues. These cutting-edge transistor-based synaptic systems offer a range of advantages including increased stability, controllable parameters, clear operation mechanisms, and construction material versatility. Concurrent learning is a huge advantage of these systems, enabling synaptic weight updates without signal transmission interruption, as well as facilitating synergistic control which allows the building of robust neural networks with fewer elements. Previously, researchers investigated a variety of materials capable of serving as artificial synapses for research and development in the field of neuromorphic computing. Magnetic multilayer structures have been viewed as highly promising materials as storage mediums for magneto-optoelectronic recording, especially Cobalt-Platinum (Co-Pt) multilayers [easily produced using DC and RF Magnetron sputtering]. The Electrolyte (DEME-TFSI) is electrically insulating but ionically conductive, so free ions wander in response to an applied gate voltage. Over the course of this Final Year Project, metallic multilayers and gate electrolytes have been examined and tested to identify potential neuromorphic electronic solutions. This report examines potentially brain-like structures and their cognitive behaviour including learning, forgetting, and relearning, as well as synaptic behaviour such as short and long-term plasticity. Area Transfer curves, gate voltage hysteresis loops, and multilevel resistance modulation were studied, and biological functions including long-term potentiation and Depression (LTP and LTD), Excitatory and Inhibitory Postsynaptic Current (EPSC and IPSC), Spike Amplitude and Duration Dependent Plasticity (SADP and SDDP), Paired Pulse Facilitation and Depression (PPF and PPD), and repeated learning and forgetting curves were emulated by our novel device. Furthermore, these functions are regulated by gate voltage application, such as by varying pulse number, interval, duration, and amplitude. Bachelor's degree 2024-05-03T02:58:43Z 2024-05-03T02:58:43Z 2024 Final Year Project (FYP) Datta, I. (2024). Synaptic devices towards neuromorphic electronics. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175688 https://hdl.handle.net/10356/175688 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Physics
Artificial synapses
Electrolyte gating
spellingShingle Physics
Artificial synapses
Electrolyte gating
Datta, Indira
Synaptic devices towards neuromorphic electronics
description New research has introduced neuromorphic systems that use artificial synapses as devices to carry out the development of platforms for interfacing biological tissues. These cutting-edge transistor-based synaptic systems offer a range of advantages including increased stability, controllable parameters, clear operation mechanisms, and construction material versatility. Concurrent learning is a huge advantage of these systems, enabling synaptic weight updates without signal transmission interruption, as well as facilitating synergistic control which allows the building of robust neural networks with fewer elements. Previously, researchers investigated a variety of materials capable of serving as artificial synapses for research and development in the field of neuromorphic computing. Magnetic multilayer structures have been viewed as highly promising materials as storage mediums for magneto-optoelectronic recording, especially Cobalt-Platinum (Co-Pt) multilayers [easily produced using DC and RF Magnetron sputtering]. The Electrolyte (DEME-TFSI) is electrically insulating but ionically conductive, so free ions wander in response to an applied gate voltage. Over the course of this Final Year Project, metallic multilayers and gate electrolytes have been examined and tested to identify potential neuromorphic electronic solutions. This report examines potentially brain-like structures and their cognitive behaviour including learning, forgetting, and relearning, as well as synaptic behaviour such as short and long-term plasticity. Area Transfer curves, gate voltage hysteresis loops, and multilevel resistance modulation were studied, and biological functions including long-term potentiation and Depression (LTP and LTD), Excitatory and Inhibitory Postsynaptic Current (EPSC and IPSC), Spike Amplitude and Duration Dependent Plasticity (SADP and SDDP), Paired Pulse Facilitation and Depression (PPF and PPD), and repeated learning and forgetting curves were emulated by our novel device. Furthermore, these functions are regulated by gate voltage application, such as by varying pulse number, interval, duration, and amplitude.
author2 Wang Xiao, Renshaw
author_facet Wang Xiao, Renshaw
Datta, Indira
format Final Year Project
author Datta, Indira
author_sort Datta, Indira
title Synaptic devices towards neuromorphic electronics
title_short Synaptic devices towards neuromorphic electronics
title_full Synaptic devices towards neuromorphic electronics
title_fullStr Synaptic devices towards neuromorphic electronics
title_full_unstemmed Synaptic devices towards neuromorphic electronics
title_sort synaptic devices towards neuromorphic electronics
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/175688
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