Atomic Layer Deposited Hf0.5Zr0.5O2-based Flexible Memristor with Short/Long-Term Synaptic Plasticity

Artificial synapses are the fundamental of building a neuron network for neuromorphic computing to overcome the bottleneck of the von Neumann system. Based on a low-temperature atomic layer deposition process, a flexible electrical synapse was proposed and showed bipolar resistive switching characte...

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Published inNanoscale research letters Vol. 14; no. 1; pp. 102 - 6
Main Authors Wang, Tian-Yu, Meng, Jia-Lin, He, Zhen-Yu, Chen, Lin, Zhu, Hao, Sun, Qing-Qing, Ding, Shi-Jin, Zhang, David Wei
Format Journal Article
LanguageEnglish
Published New York Springer US 15.03.2019
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Abstract Artificial synapses are the fundamental of building a neuron network for neuromorphic computing to overcome the bottleneck of the von Neumann system. Based on a low-temperature atomic layer deposition process, a flexible electrical synapse was proposed and showed bipolar resistive switching characteristics. With the formation and rupture of ions conductive filaments path, the conductance was modulated gradually. Under a series of pre-synaptic spikes, the device successfully emulated remarkable short-term plasticity, long-term plasticity, and forgetting behaviors. Therefore, memory and learning ability were integrated to the single flexible memristor, which are promising for the next-generation of artificial neuromorphic computing systems.
AbstractList Artificial synapses are the fundamental of building a neuron network for neuromorphic computing to overcome the bottleneck of the von Neumann system. Based on a low-temperature atomic layer deposition process, a flexible electrical synapse was proposed and showed bipolar resistive switching characteristics. With the formation and rupture of ions conductive filaments path, the conductance was modulated gradually. Under a series of pre-synaptic spikes, the device successfully emulated remarkable short-term plasticity, long-term plasticity, and forgetting behaviors. Therefore, memory and learning ability were integrated to the single flexible memristor, which are promising for the next-generation of artificial neuromorphic computing systems.
Abstract Artificial synapses are the fundamental of building a neuron network for neuromorphic computing to overcome the bottleneck of the von Neumann system. Based on a low-temperature atomic layer deposition process, a flexible electrical synapse was proposed and showed bipolar resistive switching characteristics. With the formation and rupture of ions conductive filaments path, the conductance was modulated gradually. Under a series of pre-synaptic spikes, the device successfully emulated remarkable short-term plasticity, long-term plasticity, and forgetting behaviors. Therefore, memory and learning ability were integrated to the single flexible memristor, which are promising for the next-generation of artificial neuromorphic computing systems.
Artificial synapses are the fundamental of building a neuron network for neuromorphic computing to overcome the bottleneck of the von Neumann system. Based on a low-temperature atomic layer deposition process, a flexible electrical synapse was proposed and showed bipolar resistive switching characteristics. With the formation and rupture of ions conductive filaments path, the conductance was modulated gradually. Under a series of pre-synaptic spikes, the device successfully emulated remarkable short-term plasticity, long-term plasticity, and forgetting behaviors. Therefore, memory and learning ability were integrated to the single flexible memristor, which are promising for the next-generation of artificial neuromorphic computing systems.Artificial synapses are the fundamental of building a neuron network for neuromorphic computing to overcome the bottleneck of the von Neumann system. Based on a low-temperature atomic layer deposition process, a flexible electrical synapse was proposed and showed bipolar resistive switching characteristics. With the formation and rupture of ions conductive filaments path, the conductance was modulated gradually. Under a series of pre-synaptic spikes, the device successfully emulated remarkable short-term plasticity, long-term plasticity, and forgetting behaviors. Therefore, memory and learning ability were integrated to the single flexible memristor, which are promising for the next-generation of artificial neuromorphic computing systems.
ArticleNumber 102
Author Wang, Tian-Yu
Sun, Qing-Qing
Chen, Lin
Ding, Shi-Jin
Zhang, David Wei
Meng, Jia-Lin
He, Zhen-Yu
Zhu, Hao
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Keywords Atomic layer deposition
Low-temperature process
Flexible electronics
Synaptic plasticity
Language English
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Snippet Artificial synapses are the fundamental of building a neuron network for neuromorphic computing to overcome the bottleneck of the von Neumann system. Based on...
Abstract Artificial synapses are the fundamental of building a neuron network for neuromorphic computing to overcome the bottleneck of the von Neumann system....
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SubjectTerms Applications of Atomic Layer Deposition
Artificial intelligence
Atomic layer deposition
Atomic layer epitaxy
Chemistry and Materials Science
Computation
Conductance
Electrodes
Filaments
Flexible electronics
Learning
Low temperature
Low-temperature process
Materials Science
Memristors
Molecular Medicine
Nano Express
Nanochemistry
Nanoscale Science and Technology
Nanotechnology
Nanotechnology and Microengineering
Neuromorphic computing
Plasticity
Polyethylene terephthalate
Resistance
Synapses
Synaptic plasticity
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Title Atomic Layer Deposited Hf0.5Zr0.5O2-based Flexible Memristor with Short/Long-Term Synaptic Plasticity
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https://pubmed.ncbi.nlm.nih.gov/PMC6420527
https://doaj.org/article/5715238dd34b40e189e23459076c93c7
Volume 14
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