Researchers have identified six new altermagnets, a class of materials with unique magnetic properties, by developing a novel machine-learning screening pipeline. This new method addresses a flaw in previous approaches where slight structural distortions in DFT-relaxed materials could mask the exact rotational symmetry defining altermagnetism. The pipeline uses experimentally determined magnetic structures and crystal-only descriptors to filter candidates, followed by spin-polarized DFT+U calculations for confirmation. The identified materials, including double perovskites, a layered cobaltite, a pyrochlore-derived molybdate, and oxyfluorides, exhibit significant momentum-dependent spin splitting. AI
IMPACT This discovery could advance spintronics research by expanding the material base for altermagnets.
RANK_REASON The cluster describes a new research methodology and the discovery of new materials through computational screening and DFT calculations, fitting the research bucket. [lever_c_demoted from research: ic=1 ai=1.0]
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