Programmable Synaptic Metaplasticity and below Femtojoule Spiking Energy Realized in Graphene-Based Neuromorphic Memristor

Bo Liu; Zhiwei Liu; In Shiang Chiu; Mengfu Di; Yongren Wu; Jer Chyi Wang; Tuo-Hung Hou; Chao Sung Lai

doi:10.1021/acsami.8b04685

Programmable Synaptic Metaplasticity and below Femtojoule Spiking Energy Realized in Graphene-Based Neuromorphic Memristor

Bo Liu, Zhiwei Liu, In Shiang Chiu, Mengfu Di, Yongren Wu, Jer Chyi Wang, Tuo-Hung Hou^*, Chao Sung Lai

^*Corresponding author for this work

Institute of Electronics

Research output: Contribution to journal › Article › peer-review

71 Scopus citations

Abstract

Memristors with rich interior dynamics of ion migration are promising for mimicking various biological synaptic functions in neuromorphic hardware systems. A graphene-based memristor shows an extremely low energy consumption of less than a femtojoule per spike, by taking advantage of weak surface van der Waals interaction of graphene. The device also shows an intriguing programmable metaplasticity property in which the synaptic plasticity depends on the history of the stimuli and yet allows rapid reconfiguration via an immediate stimulus. This graphene-based memristor could be a promising building block toward designing highly versatile and extremely energy efficient neuromorphic computing systems.

Original language	English
Pages (from-to)	20237-20243
Number of pages	7
Journal	ACS Applied Materials and Interfaces
Volume	10
Issue number	24
DOIs	https://doi.org/10.1021/acsami.8b04685
State	Published - 20 Jun 2018

Keywords

artificial synapses
below femtojoule spiking energy
graphene electrode
neuromorphic memristor
programmable metaplasticity
spike-timing dependent plasticity

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1021/acsami.8b04685

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title = "Programmable Synaptic Metaplasticity and below Femtojoule Spiking Energy Realized in Graphene-Based Neuromorphic Memristor",

abstract = "Memristors with rich interior dynamics of ion migration are promising for mimicking various biological synaptic functions in neuromorphic hardware systems. A graphene-based memristor shows an extremely low energy consumption of less than a femtojoule per spike, by taking advantage of weak surface van der Waals interaction of graphene. The device also shows an intriguing programmable metaplasticity property in which the synaptic plasticity depends on the history of the stimuli and yet allows rapid reconfiguration via an immediate stimulus. This graphene-based memristor could be a promising building block toward designing highly versatile and extremely energy efficient neuromorphic computing systems.",

keywords = "artificial synapses, below femtojoule spiking energy, graphene electrode, neuromorphic memristor, programmable metaplasticity, spike-timing dependent plasticity",

author = "Bo Liu and Zhiwei Liu and Chiu, {In Shiang} and Mengfu Di and Yongren Wu and Wang, {Jer Chyi} and Tuo-Hung Hou and Lai, {Chao Sung}",

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doi = "10.1021/acsami.8b04685",

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AU - Liu, Zhiwei

AU - Chiu, In Shiang

AU - Di, Mengfu

AU - Wu, Yongren

AU - Wang, Jer Chyi

AU - Hou, Tuo-Hung

AU - Lai, Chao Sung

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AB - Memristors with rich interior dynamics of ion migration are promising for mimicking various biological synaptic functions in neuromorphic hardware systems. A graphene-based memristor shows an extremely low energy consumption of less than a femtojoule per spike, by taking advantage of weak surface van der Waals interaction of graphene. The device also shows an intriguing programmable metaplasticity property in which the synaptic plasticity depends on the history of the stimuli and yet allows rapid reconfiguration via an immediate stimulus. This graphene-based memristor could be a promising building block toward designing highly versatile and extremely energy efficient neuromorphic computing systems.

KW - artificial synapses

KW - below femtojoule spiking energy

KW - graphene electrode

KW - neuromorphic memristor

KW - programmable metaplasticity

KW - spike-timing dependent plasticity

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Programmable Synaptic Metaplasticity and below Femtojoule Spiking Energy Realized in Graphene-Based Neuromorphic Memristor

Abstract

Keywords

UN SDGs

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