Literature DB >> 29557440

A compact skyrmionic leaky-integrate-fire spiking neuron device.

Xing Chen1, Wang Kang1, Daoqian Zhu1, Xichao Zhang2, Na Lei1, Youguang Zhang1, Yan Zhou2, Weisheng Zhao1.   

Abstract

Neuromorphic computing, which relies on a combination of a large number of neurons massively interconnected by an even larger number of synapses, has been actively studied for its characteristics such as energy efficiency, intelligence, and adaptability. To date, while the development of artificial synapses has shown great progress with the introduction of emerging nanoelectronic devices, e.g., memristive devices, the implementation of artificial neurons, however, depends mostly on semiconductor-based circuits via integrating many transistors, sacrificing energy efficiency and integration density. Here, we present a novel compact neuron device that exploits the current-driven magnetic skyrmion dynamics in a wedge-shaped nanotrack. Under the coaction of the exciting current pulse and the repulsive force exerted by the nanotrack edges, the dynamic behavior of the proposed skyrmionic artificial neuron device is in analogy to the leaky-integrate-fire (LIF) spiking function of a biological neuron. The tunable temporary location of the skyrmion in our artificial neuron behaves like the analog membrane potential of a biological neuron. The neuronal dynamics and the related physical interpretations of the proposed skyrmionic neuron device are carefully investigated via micromagnetic and theoretical methods. Such a compact artificial neuron enables energy-efficient and high-density implementation of neuromorphic computing hardware.

Mesh:

Year:  2018        PMID: 29557440     DOI: 10.1039/C7NR09722K

Source DB:  PubMed          Journal:  Nanoscale        ISSN: 2040-3364            Impact factor:   7.790


  5 in total

1.  Friedel Oscillations Induced by Magnetic Skyrmions: From Scattering Properties to All-Electrical Detection.

Authors:  Mohammed Bouhassoune; Samir Lounis
Journal:  Nanomaterials (Basel)       Date:  2021-01-14       Impact factor: 5.076

2.  Tailoring interfacial effect in multilayers with Dzyaloshinskii-Moriya interaction by helium ion irradiation.

Authors:  A Sud; S Tacchi; D Sagkovits; C Barton; M Sall; L H Diez; E Stylianidis; N Smith; L Wright; S Zhang; X Zhang; D Ravelosona; G Carlotti; H Kurebayashi; O Kazakova; M Cubukcu
Journal:  Sci Rep       Date:  2021-12-08       Impact factor: 4.379

3.  Machine learning with a snapshot of data: Spiking neural network 'predicts' reinforcement histories of pigeons' choice behavior.

Authors:  Anna Plessas; Josafath I Espinosa-Ramos; Dave Parry; Sarah Cowie; Jason Landon
Journal:  J Exp Anal Behav       Date:  2022-04-21       Impact factor: 2.215

4.  Voltage-controlled skyrmion-based nanodevices for neuromorphic computing using a synthetic antiferromagnet.

Authors:  Ziyang Yu; Maokang Shen; Zhongming Zeng; Shiheng Liang; Yong Liu; Ming Chen; Zhenhua Zhang; Zhihong Lu; Long You; Xiaofei Yang; Yue Zhang; Rui Xiong
Journal:  Nanoscale Adv       Date:  2020-02-07

Review 5.  Magnetic Elements for Neuromorphic Computing.

Authors:  Tomasz Blachowicz; Andrea Ehrmann
Journal:  Molecules       Date:  2020-05-30       Impact factor: 4.411

  5 in total

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