2026-06-01T19:58:05Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/47612024-07-24T11:19:55Zcom_10259_9476com_10259.4_106com_10259_2604col_10259_9477

00925njm 22002777a 4500 dc Arapan, Sergiu author Nieves Cordones, Pablo author Cuesta López, Santiago author 2018-02 We study the capability of a structure predicting method based on genetic/evolutionary algorithm for a high-throughput exploration of magnetic materials. We use the USPEX and VASP codes to predict stable and generate low-energy meta-stable structures for a set of representative magnetic structures comprising intermetallic alloys, oxides, interstitial compounds, and systems containing rare-earths elements, and for both types of ferromagnetic and antiferromagnetic ordering. We have modified the interface between USPEX and VASP codes to improve the performance of structural optimization as well as to perform calculations in a high-throughput manner. We show that exploring the structure phase space with a structure predicting technique reveals large sets of low-energy metastable structures, which not only improve currently exiting databases, but also may provide understanding and solutions to stabilize and synthesize magnetic materials suitable for permanent magnet applications. 0021-8979 http://hdl.handle.net/10259/4761 10.1063/1.5004979 A high-throughput exploration of magnetic materials by using structure predicting methods