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In the field of spintronics, there is a strong demand for barrier materials in magnetic tunnel junctions (MTJs) having high tunnel magnetoresistance (TMR) and low resistance area product (RA). However, the design of such barrier materials with atomically controlled composition, vacancies, and disordering of the constituent elements is still challenging due to the combinatorial explosion of potential candidates. Very recently, a quantum annealing (QA) method has been utilized for combinatorial optimization problems in materials science. In this paper, we perform a proof-of-concept study by applying the QA approach combining with first-principles calculations and a machine-learning factorization machine (FM) to MTJs with inverse-type spinel MgGa2O4 tunnel barrier. We treat 252 combinations of Mg2+ and Ga3+ cation disordering in the barrier layer of the MTJs and discuss the effect of the cation disordering on the structural stability, TMR, and RA. Our method is superior to simulated annealing, Bayesian optimization, and
random sampling in searching for the best MTJs for low total energy and high TMR, but not so for low RA. We also revealed physical origins of high TMR and low RA behind the cation disordering. The present work highlights the applicability and advantage of materials informatics using FM+QA with first-principles calculations in designing spintronic MTJ devices.

権利情報:

• Creative Commons BY Attribution 4.0 International
  

キーワード: Magnetic tunnel junctions, Adiabatic quantum optimization, Quantum computation, Spintronics

刊行年月日: 2023-08-17

出版者: American Physical Society (APS)

掲載誌:

• Physical Review Applied (ISSN: 23317019) vol. 20 issue. 2 024044

研究助成金:

• National Institute of Advanced Industrial Science and Technology
• NIMS
• KAKENHI JP20H02190
• KAKENHI JP20K14782
• KAKENHI JP21H01750
• KAKENHI JP21K03391
• KAKENHI JP22H04966
• Numerical Materials Simulator
• KAKENHI JP22K14290
• KAKENHI JP23H05447
• KAKENHI JP23K03933
• MEXT
• TDK Corporation
• Data-Science Research Center
• Material, Quantum, and Measurement Technologies, Mie University

原稿種別: 出版者版 (Version of record)

MDR DOI:

公開URL: https://doi.org/10.1103/physrevapplied.20.024044

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更新時刻: 2024-05-25 08:30:14 +0900

MDRでの公開時刻: 2024-05-25 08:30:14 +0900