Literature DB >> 32904074

Short Communication: An Updated Design to Implement Artificial Neuron Synaptic Behaviors in One Device with a Control Gate.

Shaocheng Qi1, Yongbin Hu1, Chaoqi Dai1, Peiqin Chen1, Zhendong Wu1, Thomas J Webster2, Mingzhi Dai1,3.   

Abstract

BACKGROUND: As a key component in artificial intelligence computing, a transistor design is updated here as a potential alternative candidate for artificial synaptic behavior implementation. However, further updates are needed to better control artificial synaptic behavior. Here, an updated channel-electrode transistor design is proposed as an artificial synapse device; this structure is different from previously published designs by other groups.
METHODS: A semiconductor characterization system was used in order to simulate the artificial synaptic behavior and a scanning electron microscope was used to characterize the device structure.
RESULTS: It was found that the electrode added to the transistor channel had a strong impact on the representative transmission behavior of such artificial synaptic devices, such as excitatory postsynaptic current (EPSC) and the paired-pulse facilitation (PPF) index.
CONCLUSION: These behaviors were tuned effectively and the impact of the channel electrode is explained by the combined effects of the joint channel electrode and conventional gate. The voltage dependence of such oxide devices suggests more capability to emulate various synaptic behaviors for numerous medical and non-medical applications. This is extremely helpful for future neuromorphic computational system implementation.
© 2020 Qi et al.

Entities:  

Keywords:  artificial synapse; channel-electrode transistor; neuron behavior control; thin-film transistor

Mesh:

Substances:

Year:  2020        PMID: 32904074      PMCID: PMC7450203          DOI: 10.2147/IJN.S223651

Source DB:  PubMed          Journal:  Int J Nanomedicine        ISSN: 1176-9114


  21 in total

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Authors:  M Ouyang; J L Huang; C L Cheung; C M Lieber
Journal:  Science       Date:  2001-04-27       Impact factor: 47.728

2.  Gated three-terminal device architecture to eliminate persistent photoconductivity in oxide semiconductor photosensor arrays.

Authors:  Sanghun Jeon; Seung-Eon Ahn; Ihun Song; Chang Jung Kim; U-In Chung; Eunha Lee; Inkyung Yoo; Arokia Nathan; Sungsik Lee; John Robertson; Kinam Kim
Journal:  Nat Mater       Date:  2012-02-26       Impact factor: 43.841

3.  Freestanding Artificial Synapses Based on Laterally Proton-Coupled Transistors on Chitosan Membranes.

Authors:  Yang Hui Liu; Li Qiang Zhu; Ping Feng; Yi Shi; Qing Wan
Journal:  Adv Mater       Date:  2015-08-25       Impact factor: 30.849

4.  Organic Synapses for Neuromorphic Electronics: From Brain-Inspired Computing to Sensorimotor Nervetronics.

Authors:  Yeongjun Lee; Tae-Woo Lee
Journal:  Acc Chem Res       Date:  2019-03-21       Impact factor: 22.384

5.  A Hybrid CMOS-Memristor Neuromorphic Synapse.

Authors:  Mostafa Rahimi Azghadi; Bernabe Linares-Barranco; Derek Abbott; Philip H W Leong
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2016-12-22       Impact factor: 3.833

6.  Artificial Synapses Emulated by an Electrolyte-Gated Tungsten-Oxide Transistor.

Authors:  Jing-Ting Yang; Chen Ge; Jian-Yu Du; He-Yi Huang; Meng He; Can Wang; Hui-Bin Lu; Guo-Zhen Yang; Kui-Juan Jin
Journal:  Adv Mater       Date:  2018-07-04       Impact factor: 30.849

Review 7.  Oxide semiconductor thin-film transistors: a review of recent advances.

Authors:  E Fortunato; P Barquinha; R Martins
Journal:  Adv Mater       Date:  2012-05-10       Impact factor: 30.849

8.  Organic core-sheath nanowire artificial synapses with femtojoule energy consumption.

Authors:  Wentao Xu; Sung-Yong Min; Hyunsang Hwang; Tae-Woo Lee
Journal:  Sci Adv       Date:  2016-06-17       Impact factor: 14.136

9.  Realization of tunable artificial synapse and memory based on amorphous oxide semiconductor transistor.

Authors:  Mingzhi Dai; Weiliang Wang; Pengjun Wang; Muhammad Zahir Iqbal; Nasim Annabi; Nasir Amin
Journal:  Sci Rep       Date:  2017-09-08       Impact factor: 4.379

10.  Flexible three-dimensional artificial synapse networks with correlated learning and trainable memory capability.

Authors:  Chaoxing Wu; Tae Whan Kim; Hwan Young Choi; Dmitri B Strukov; J Joshua Yang
Journal:  Nat Commun       Date:  2017-09-29       Impact factor: 14.919

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