Elucidating proximity magnetism through polarized neutron reflectometry and machine learning

Andrejevic, Nina; Chen, Zhantao; Nguyen, Thanh; Fan, Leon; Heiberger, Henry; Zhou, Ling-Jie; Zhao, Yi-Fan; Chang, Cui-Zu; Grutter, Alexander; Li, Mingda

doi:10.1063/5.0078814

Elucidating proximity magnetism through polarized neutron reflectometry and machine learning

Journal Article · Thu Mar 17 00:00:00 EDT 2022 · Applied Physics Reviews

DOI:https://doi.org/10.1063/5.0078814· OSTI ID:2564794

; Chen, Zhantao; ; Fan, Leon; Heiberger, Henry; ; Zhao, Yi-Fan; Chang, Cui-Zu; ;

Polarized neutron reflectometry is a powerful technique to interrogate the structures of multilayered magnetic materials with depth sensitivity and nanometer resolution. However, reflectometry profiles often inhabit a complicated objective function landscape using traditional fitting methods, posing a significant challenge for parameter retrieval. In this work, we develop a data-driven framework to recover the sample parameters from polarized neutron reflectometry data with minimal user intervention. We train a variational autoencoder to map reflectometry profiles with moderate experimental noise to an interpretable, low-dimensional space from which sample parameters can be extracted with high resolution. We apply our method to recover the scattering length density profiles of the topological insulator–ferromagnetic insulator heterostructure Bi2Se3/EuS exhibiting proximity magnetism in good agreement with the results of conventional fitting. We further analyze a more challenging reflectometry profile of the topological insulator–antiferromagnet heterostructure (Bi,Sb)2Te3/Cr2O3 and identify possible interfacial proximity magnetism in this material. We anticipate that the framework developed here can be applied to resolve hidden interfacial phenomena in a broad range of layered systems.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: SC0020148; SC0021940

OSTI ID:: 2564794

Alternate ID(s):: OSTI ID: 1855545
OSTI ID: 1979015

Journal Information:: Applied Physics Reviews, Journal Name: Applied Physics Reviews Journal Issue: 1 Vol. 9; ISSN 1931-9401

Publisher:: American Institute of PhysicsCopyright Statement

Country of Publication:: United States

Language:: English

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