Perpendicular-spin-transfer-torque magnetic-tunnel-junction neuron for spiking neural networks depending on the nanoscale grain size of the MgO tunnelling barrier-Reference-Cited by-同舟云学术

Perpendicular-spin-transfer-torque magnetic-tunnel-junction neuron for spiking neural networks depending on the nanoscale grain size of the MgO tunnelling barrier

Published:2022 Issue:3 Volume:3 Page:1587-1593
ISSN:2633-5409
Container-title:Materials Advances
language:en
Short-container-title:Mater. Adv.

Author:

Baek Jong-Ung¹,Choi Jin-Young²,Kim Dong-Won¹^ORCID,Kim Ji-Chan²,Jun Han-Sol¹,Woo Dae-Seong¹^ORCID,Yi Woo-Seok³^ORCID,Choi Yo-Han¹,Seo Hyung-Tak⁴^ORCID,Kim Jae-Joon⁵,Park Jea-Gun¹²^ORCID

Affiliation:

1. Department of Nanoscale Semiconductor Engineering, Hanyang University, Seoul, 04763, Republic of Korea

2. Department of Electronic Engineering, Hanyang University, Seoul, 04763, Republic of Korea

3. Department of Creative IT Engineering, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea

4. Department of Electrical and Computer Engineering, Seoul National University, Seoul, 08826, Republic of Korea

5. Department of Energy Systems Research & Materials Science and Engineering, Ajou University, Suwon, 16499, Republic of Korea

Abstract

The perpendicular-spin-transfer-torque magnetic-tunnel-junction neuron exhibited integrate behaviour depending on the nanoscale grain size of the MgO tunnelling barrier showing possibility for spiking neural network applications.

Funder

National Research Foundation of Korea

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science,Chemistry (miscellaneous)

Link

http://pubs.rsc.org/en/content/articlepdf/2022/MA/D1MA00862E

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