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

Shenghong Ju,Junichiro Shiomi,Yoshio Miura,Ken-ichi Uchida,Keisuke Masuda,Kaoru Yamamoto

doi:10.1103/physrevresearch.2.023187

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/disordered-MgAl2O4(MAO)/Fe(001) magnetic tunnel junctions (MTJs) to determine 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 {\Delta}1 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 material informatics combined with first-principles transport calculations in designing high-performance spintronic devices based on MTJs.

Highlights

Magnetic tunnel junctions (MTJs), which exhibit different resistance depending on the relative magnetization directions of the ferromagnetic electrodes, are among the most important devices for spintronic applications, such as magnetic random access memories (MRAMs) and high-sensitivity magnetic sensors [1,2]
The tunnel magnetoresistance (TMR) ratio of Fe/disordered-MAO/Fe magnetic tunnel junctions (MTJs) is successfully optimized by Bayesian optimization
The maximum TMR ratio obtained is over 600%, which is much larger than the TMR ratio of Fe/ordered-MAO/Fe MTJs (160%)

Summary

Introduction

Magnetic tunnel junctions (MTJs), which exhibit different resistance depending on the relative magnetization directions of the ferromagnetic electrodes, are among the most important devices for spintronic applications, such as magnetic random access memories (MRAMs) and high-sensitivity magnetic sensors [1,2]. MgO-based MTJs have yielded large tunnel magnetoresistance (TMR) ratios of over 600% at room temperature due to coherent tunneling through the 1 evanescent state of MgO and the half-metallic behavior of the 1 state. Epitaxial growth of crystalline MgO is difficult because of its lattice mismatch with the ferromagnetic electrode, which is about 4% for bcc-Fe and over 5% for half-metallic Co-based full Heusler alloys. Sukegawa and co-workers have fabricated new epitaxial barrier layers, MgAl2O4 on Fe electrodes, and initially observed a TMR ratio of about 165% at 15 K [7]. Normal spinel-type MgAl2O4 (MAO) has two different cation sites: tetragonal A-sites and octahedral B-sites. The lattice constant of the spinel barrier can be modulated by choosing various metallic elements for the cation atoms in A-site and B-site, making it a promising candidate for the new barrier layer

Methods

Results

Conclusion