ABN_(3)-type nitride perovskites offer a rich platform for multifunctional materials but remain synthetically elusive.Here,we develop a machine learning(ML)-guided framework to expand the library of nitride perovskite...ABN_(3)-type nitride perovskites offer a rich platform for multifunctional materials but remain synthetically elusive.Here,we develop a machine learning(ML)-guided framework to expand the library of nitride perovskites and identify multiferroic candidates.By integrating positive-unlabeled(PU)learning with crystal graph convolutional neural networks(CGCNN),we screen 1465 ABN_(3)compositions and predict 96 synthesizable compounds.Further symmetry and magnetic filtering yield 4 altermagnetic ferroelectric(AM-FE)perovskites.Among them,CeCrN_(3)emerges as a promising candidate,exhibiting a bandgap of 0.30 eV,a spontaneous polarization of 0.59μC/cm^(2),a high Curie temperature of 650 K,and a low polarization switching barrier of 53 meV,as confirmed by density functional theory(DFT)calculations.In addition,CeCrN_(3)demonstrates a pronounced bulk photovoltaic effect(BPVE),with the shift current reaching 44μA/V^(2)and an injection current reaching 2.4×10^(9)A/V^(2),both of which reverse upon FE switching.These findings not only advance the understanding of nitride perovskites but also provides a validated ML-DFT framework to guide experimental efforts in realizing novel functional materials.展开更多
基金the Shenzhen Natural Science Fund(the Stable Support Plan Program 20231121110218001)China Postdoctoral Science Foundation(2023M742403)for financial support.
文摘ABN_(3)-type nitride perovskites offer a rich platform for multifunctional materials but remain synthetically elusive.Here,we develop a machine learning(ML)-guided framework to expand the library of nitride perovskites and identify multiferroic candidates.By integrating positive-unlabeled(PU)learning with crystal graph convolutional neural networks(CGCNN),we screen 1465 ABN_(3)compositions and predict 96 synthesizable compounds.Further symmetry and magnetic filtering yield 4 altermagnetic ferroelectric(AM-FE)perovskites.Among them,CeCrN_(3)emerges as a promising candidate,exhibiting a bandgap of 0.30 eV,a spontaneous polarization of 0.59μC/cm^(2),a high Curie temperature of 650 K,and a low polarization switching barrier of 53 meV,as confirmed by density functional theory(DFT)calculations.In addition,CeCrN_(3)demonstrates a pronounced bulk photovoltaic effect(BPVE),with the shift current reaching 44μA/V^(2)and an injection current reaching 2.4×10^(9)A/V^(2),both of which reverse upon FE switching.These findings not only advance the understanding of nitride perovskites but also provides a validated ML-DFT framework to guide experimental efforts in realizing novel functional materials.
