2021年第68回応用物理学会春季学術講演会

講演情報

一般セッション(口頭講演)

10 スピントロニクス・マグネティクス » 10.1 新物質・新機能創成(作製・評価技術)

[16p-Z19-1~23] 10.1 新物質・新機能創成(作製・評価技術)

2021年3月16日(火) 13:00 〜 19:30 Z19 (Z19)

小峰 啓史(茨城大)、介川 裕章(物材機構)、羽尻 哲也(名大)、井口 亮(物材機構)

19:00 〜 19:15

[16p-Z19-22] Determination of the Dzyaloshinskii-Moriya interaction from a single magnetic domain image using image recognition

Masashi Kawaguchi1、Kenji Tanabe2、Keisuke Yamada3、Takuya Sawa2、Shun Hasegawa1、Masamitsu Hayashi1、Yoshinobu Nakatani4 (1.The Univ. of Tokyo、2.TTI、3.Gifu Univ.、4.UEC)

キーワード:spintronics, Dzyaloshinskii-Moriya interaction, machine learning

The Dzyaloshinskii-Moriya interaction (DMI) , generating chiral magnetic orders in symmetry broken ferromagnetic multilayers, has been studied intensively. A great deal of effort has been spent on evaluation of DMI due to its difficulty. A simple and accurate evaluation method accelerate spintronics device development. In this study, we demonstrate determination of DMI strength from a single magnetic domain image employing image recognition supported by machine learning. A convolution neural network (CNN), trained with data sets prepared by micromagnetic simulations, can estimate the DMI strength of testing data sets with accuracy ~ 0.05mJ/m2. Image recognition of magnetic domain patterns using CNN is applied to experimental systems that consist of Pt/Co based ferromagnetic multilayers, and returns consistent DMI strength.