Nanoscale conductive filament with alternating rectification as an artificial synapse building block
A popular approach for resistive memory (RRAM)-based hardware implementation of neural networks utilizes one (or two) device that functions as an analog synapse in a crossbar structure of perpendicular pre- and postsynaptic neurons. An ideal fully automated, large-scale artificial neural network, wh...
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sg-ntu-dr.10356-1435942020-09-14T01:32:00Z Nanoscale conductive filament with alternating rectification as an artificial synapse building block Berco, Dan Zhou, Yu Gollu, Sankara Rao Kalaga, Pranav Sairam Kole, Abhisek Mohamed Hassan Ang, Diing Shenp School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Synaptic Gap Junctions Electrical Synapses A popular approach for resistive memory (RRAM)-based hardware implementation of neural networks utilizes one (or two) device that functions as an analog synapse in a crossbar structure of perpendicular pre- and postsynaptic neurons. An ideal fully automated, large-scale artificial neural network, which matches a biologic counterpart (in terms of density and energy consumption), thus requires nanosized, extremely low power devices with a wide dynamic range and multilevel functionality. Unfortunately the trade-off between these traits proves to be a serious obstacle in the realization of brain-inspired computing platforms yet to be overcome. This study demonstrates an alternative manner for the implementation of artificial synapses in which the local stoichiometry of metal oxide materials is delicately manipulated to form a single nanoscale conductive filament that may be used as a synaptic gap building block in an equivalent manner to the functionality of a single connexon (a signaling pore between synapses) with dynamic rectification direction. The structure, of a few nanometers in size, is based on the formation of defect states and shows current rectification properties that can be consecutively flipped to a forward or reverse direction to create either an excitatory or inhibitory (positive or negative) weight parameter. Alternatively, a plurality of these artificial connexons may be used to create a synthetic rectifying synaptic gap junction. In addition, the junction plasticity may be altered in a differential digital scheme (opposed to conventional analog RRAM conductivity manipulation) by changing the ratio of forward to reverse rectifying connexons. 2020-09-14T01:32:00Z 2020-09-14T01:32:00Z 2018 Journal Article Berco, D., Zhou, Y., Gollu, S. R., Kalaga, P. S., Kole, A., Mohamed Hassan, & Ang, D. S. (2018). Nanoscale conductive filament with alternating rectification as an artificial synapse building block. ACS Nano, 12(6), 5946-5955. doi:10.1021/acsnano.8b02193 1936-086X https://hdl.handle.net/10356/143594 10.1021/acsnano.8b02193 29792707 6 12 5946 5955 en ACS Nano © 2018 American Chemical Society. All rights reserved. |
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Engineering::Electrical and electronic engineering Synaptic Gap Junctions Electrical Synapses Berco, Dan Zhou, Yu Gollu, Sankara Rao Kalaga, Pranav Sairam Kole, Abhisek Mohamed Hassan Ang, Diing Shenp Nanoscale conductive filament with alternating rectification as an artificial synapse building block |
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A popular approach for resistive memory (RRAM)-based hardware implementation of neural networks utilizes one (or two) device that functions as an analog synapse in a crossbar structure of perpendicular pre- and postsynaptic neurons. An ideal fully automated, large-scale artificial neural network, which matches a biologic counterpart (in terms of density and energy consumption), thus requires nanosized, extremely low power devices with a wide dynamic range and multilevel functionality. Unfortunately the trade-off between these traits proves to be a serious obstacle in the realization of brain-inspired computing platforms yet to be overcome. This study demonstrates an alternative manner for the implementation of artificial synapses in which the local stoichiometry of metal oxide materials is delicately manipulated to form a single nanoscale conductive filament that may be used as a synaptic gap building block in an equivalent manner to the functionality of a single connexon (a signaling pore between synapses) with dynamic rectification direction. The structure, of a few nanometers in size, is based on the formation of defect states and shows current rectification properties that can be consecutively flipped to a forward or reverse direction to create either an excitatory or inhibitory (positive or negative) weight parameter. Alternatively, a plurality of these artificial connexons may be used to create a synthetic rectifying synaptic gap junction. In addition, the junction plasticity may be altered in a differential digital scheme (opposed to conventional analog RRAM conductivity manipulation) by changing the ratio of forward to reverse rectifying connexons. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Berco, Dan Zhou, Yu Gollu, Sankara Rao Kalaga, Pranav Sairam Kole, Abhisek Mohamed Hassan Ang, Diing Shenp |
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Article |
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Berco, Dan Zhou, Yu Gollu, Sankara Rao Kalaga, Pranav Sairam Kole, Abhisek Mohamed Hassan Ang, Diing Shenp |
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Berco, Dan |
title |
Nanoscale conductive filament with alternating rectification as an artificial synapse building block |
title_short |
Nanoscale conductive filament with alternating rectification as an artificial synapse building block |
title_full |
Nanoscale conductive filament with alternating rectification as an artificial synapse building block |
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Nanoscale conductive filament with alternating rectification as an artificial synapse building block |
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Nanoscale conductive filament with alternating rectification as an artificial synapse building block |
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nanoscale conductive filament with alternating rectification as an artificial synapse building block |
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2020 |
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https://hdl.handle.net/10356/143594 |
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