Two-dimensional(2D)transition metal oxyhalides and nitrogen-halides(T_(M)BXs,where T_(M)=transition metal,B=O-group and N-group elements,X=halogen)have emerged as promising candidates for exploring multiferroic orders...Two-dimensional(2D)transition metal oxyhalides and nitrogen-halides(T_(M)BXs,where T_(M)=transition metal,B=O-group and N-group elements,X=halogen)have emerged as promising candidates for exploring multiferroic orders and spintronic applications.In this study,we conduct a systematic firstprinciples high-throughput screening combined with machine learning to identify novel 2D ferromagnetic and multiferroic materials within T_(M)BX family.From a comprehensive dataset comprising 672 T_(M)BX monolayers,we identify 78 ferromagnetic systems,of which 38 exhibit high Curie temperatures(TC≥200 K),significantly expanding the known library of 2D magnetic materials.A machine learningmodel is developed to elucidate the key factors governing ferromagnetism,revealing that the second-nearest neighbor exchange interaction(J_(2))plays a dominant role in determining TC.Furthermore,we discovered seven ferromagnetic-ferroelectric multiferroic systems,revealing unique polarization switching pathways.Notably,spin transport simulations using the nonequilibriumGreen’s function formalism demonstrate exceptional spin filtering capabilities(~100%)and giant biasdependent tunneling magnetoresistance(>10^(5)%).These findings deepen the fundamental understanding of 2D multiferroics and establish a desired platformfor future experimental exploration and the development of next-generation spintronic devices.展开更多
基金supported by the National Science Foundation of China (Grant No. 12347115)China Postdoctoral Science Foundation (No. 2024M760690)+2 种基金Hangzhou Science and Technology Bureau of Zhejiang Province (No. TD2020002)Work at HDU was supported by Zhejiang Provincial Natural Science Foundation (QN25A040026)the Foundation of Hangzhou Dianzi University (KYS075624288). We gratefully acknowledge HZWTECH for providing computational facilities. S. Xu thanks Taozhen Fu (from HZWTECH) for help and discussions on this study.
文摘Two-dimensional(2D)transition metal oxyhalides and nitrogen-halides(T_(M)BXs,where T_(M)=transition metal,B=O-group and N-group elements,X=halogen)have emerged as promising candidates for exploring multiferroic orders and spintronic applications.In this study,we conduct a systematic firstprinciples high-throughput screening combined with machine learning to identify novel 2D ferromagnetic and multiferroic materials within T_(M)BX family.From a comprehensive dataset comprising 672 T_(M)BX monolayers,we identify 78 ferromagnetic systems,of which 38 exhibit high Curie temperatures(TC≥200 K),significantly expanding the known library of 2D magnetic materials.A machine learningmodel is developed to elucidate the key factors governing ferromagnetism,revealing that the second-nearest neighbor exchange interaction(J_(2))plays a dominant role in determining TC.Furthermore,we discovered seven ferromagnetic-ferroelectric multiferroic systems,revealing unique polarization switching pathways.Notably,spin transport simulations using the nonequilibriumGreen’s function formalism demonstrate exceptional spin filtering capabilities(~100%)and giant biasdependent tunneling magnetoresistance(>10^(5)%).These findings deepen the fundamental understanding of 2D multiferroics and establish a desired platformfor future experimental exploration and the development of next-generation spintronic devices.
