• Open Access

Machine learning analysis of tunnel magnetoresistance of magnetic tunnel junctions with disordered MgAl2O4

Shenghong Ju, Yoshio Miura, Kaoru Yamamoto, Keisuke Masuda, Ken-ichi Uchida, and Junichiro Shiomi
Phys. Rev. Research 2, 023187 – Published 19 May 2020
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Abstract

Through Bayesian optimization and the least absolute shrinkage and selection operator (LASSO) technique combined with first-principles calculations, we investigated the tunnel magnetoresistance (TMR) effect of Fe/disorderedMgAl2O4(MAO)/Fe(001) magnetic tunnel junctions (MTJs) to determine the structures of disordered-MAO that give large TMR ratios. The optimal structure with the largest TMR ratio was obtained by Bayesian optimization with 1728 structural candidates, where the convergence was reached within 300 structure calculations. Characterization of the obtained structures suggested that the in-plane distance between two Al atoms plays an important role in determining the TMR ratio. Since the Al-Al distance of disordered MAO significantly affects the imaginary part of complex band structures, the majority-spin conductance of the Δ1 state in Fe/disordered-MAO/Fe MTJs increases with increasing in-plane Al-Al distance, leading to larger TMR ratios. Furthermore, we found that the TMR ratio tended to be large when the ratio of the number of Al, Mg, and vacancies in the [001] plane was 2:1:1, indicating that the control of Al atomic positions is essential to enhancing the TMR ratio in MTJs with disordered MAO. The present work reveals the effectiveness and advantage of materials informatics combined with first-principles transport calculations in designing high-performance spintronic devices based on MTJs.

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  • Received 14 January 2020
  • Revised 25 March 2020
  • Accepted 16 April 2020

DOI:https://doi.org/10.1103/PhysRevResearch.2.023187

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied Physics

Authors & Affiliations

Shenghong Ju1,2,3, Yoshio Miura3,4,5,6,*, Kaoru Yamamoto4,6, Keisuke Masuda4,6, Ken-ichi Uchida2,3,4,6,7,8, and Junichiro Shiomi2,3,6

  • 1China-UK Low Carbon College, Shanghai Jiao Tong University, No. 3 Yinlian Road, Lingang, Shanghai 201306, China
  • 2Department of Mechanical Engineering, The University of Tokyo, 7-3-1 Hongo, Tokyo 113-8656, Japan
  • 3Center for Materials Research by Information Integration (CMI2), Research and Services Division of Materials Data and Integrated System (MaDIS), National Institute for Materials Science (NIMS), 1-2-1 Sengen, Tsukuba 305-0047, Japan
  • 4Research Center for Magnetic and Spintronic Materials, National Institute for Materials Science (NIMS), 1-2-1 Sengen, Tsukuba 305-0047, Japan
  • 5Center for Spintronics Research Network (CSRN), Graduate School of Engineering Science, Osaka University, Machikaneyama 1-3, Toyonaka, Osaka 560-8531, Japan
  • 6Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency (JST), 4-1-8, Kawaguchi, Saitama 332-0012, Japan
  • 7Institute for Materials Research, Tohoku University, Katahira 2-1-1, Sendai 980-8577, Japan
  • 8Center for Spintronics Research Network, Tohoku University, Katahira 2-1-1, Sendai 980-8577, Japan

  • *Corresponding author: MIURA.Yoshio@nims.go.jp

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Vol. 2, Iss. 2 — May - July 2020

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