High Throughput Discovery of 2D Ferromagnetic and Multiferroic Transition Metal Oxyhalides and Nitrogen Halides DOI
Shaowen Xu, Fanhao Jia, Ning Dai

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 11, 2025

Abstract Two-dimensional (2D) transition metal oxyhalides and nitrogen-halides (TMBXs, where TM = metal, B O-group N-group elements, X halogen) have emerged as promising candidates for exploring multiferroic orders spintronic applications. In this study, we conduct a systematic first-principles high-throughput screening combined with machine learning to identify novel 2D ferromagnetic materials within TMBX family. From comprehensive dataset comprising 672 monolayers, 78 systems, of which 38 exhibit high Curie temperatures (TC ≥ 200 K), significantly expanding the known library magnetic materials. A model is developed elucidate key factors governing ferromagnetism, revealing that second-nearest neighbor exchange interaction (J2) plays dominant role in determining TC. Furthermore, discover seven ferromagnetic-ferroelectric unique polarization switching pathways. Notably, spin transport simulations using nonequilibrium Green's function formalism demonstrate exceptional filtering capabilities (~ 100 %) giant bias-dependent tunneling magnetoresistance (> 105 %). These findings deepen fundamental understanding multiferroics establish solid platform future experimental exploration development next-generation devices.

Language: Английский

High Throughput Discovery of 2D Ferromagnetic and Multiferroic Transition Metal Oxyhalides and Nitrogen Halides DOI
Shaowen Xu, Fanhao Jia, Ning Dai

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 11, 2025

Abstract Two-dimensional (2D) transition metal oxyhalides and nitrogen-halides (TMBXs, where TM = metal, B O-group N-group elements, X halogen) have emerged as promising candidates for exploring multiferroic orders spintronic applications. In this study, we conduct a systematic first-principles high-throughput screening combined with machine learning to identify novel 2D ferromagnetic materials within TMBX family. From comprehensive dataset comprising 672 monolayers, 78 systems, of which 38 exhibit high Curie temperatures (TC ≥ 200 K), significantly expanding the known library magnetic materials. A model is developed elucidate key factors governing ferromagnetism, revealing that second-nearest neighbor exchange interaction (J2) plays dominant role in determining TC. Furthermore, discover seven ferromagnetic-ferroelectric unique polarization switching pathways. Notably, spin transport simulations using nonequilibrium Green's function formalism demonstrate exceptional filtering capabilities (~ 100 %) giant bias-dependent tunneling magnetoresistance (> 105 %). These findings deepen fundamental understanding multiferroics establish solid platform future experimental exploration development next-generation devices.

Language: Английский

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