https://hdl.handle.net/10259/9478 2026-04-28T16:43:04Z 2026-04-28T16:43:04Z Nieves Cordones, Pablo Arapan, Sergiu Cuesta López, Santiago https://hdl.handle.net/10259/5723 2024-07-24T11:07:08Z 2017-08-01T00:00:00Z

An adaptive genetic algorithm approach for predicting magnet-ic structure suitable for high-performance permanent magnet development Nieves Cordones, Pablo; Arapan, Sergiu; Cuesta López, Santiago Summary form only given. In this work, we present a general overview, analysis and software implementation of a particular AGA, which has been proposed for discovering new RE-free magnetic crystal phases in the context of the EU-H2020 NOVAMAG project. The workflow diagram related to the Modelling Data Elements (MODA) of the magnetic crystal structure calculation based on AGA was shown. In particular, we make use of an AGA, implemented through USPEX and VASP codes, to predict new magnetic crystal phases, where those structures with better magnetic properties for a permanent magnet are selected and analyzed in more detail. Such a methodology has been preliminary compared to well-known experimentally reported properties compounds, showing an excellent agreement. In addition, we show recent results predicted by AGA in CoFe 2n X (n=1,2,3,4,5; where X=C, P, Hf, Zr, ...), where we found compounds with many metastable structures which fulfill the initial requirements (negative enthalpy of formation ΔHF<;0, high saturation magnetization μ 0 M S >1T and non-cubic lattice system) for permanent magnet development. Trabajo presentado en: International Conference on Magnetics (INTERMAG), 2017

2017-08-01T00:00:00Z