We introduce a high-fidelity high-throughput screening (HTS) strategy to accelerate the discovery of altermagnets by combining density functional theory (DFT) with embedded dynamical mean-field theory. Our approach improves over the HTS with the conventional DFT method in the accuracy of predicting metallicity and spin splitting, especially in transition-metal-rich compounds. Our method is based on an automated workflow that incorporates prescreening and symmetry analysis and can be applied to a variety of correlated materials. This approach identified two previously unreported metallic altermagnets, CrSe and CaFe₄Al₈ (in addition to one known altermagnet CrSb), as well as a dozen semiconducting altermagnets among over 2000 magnetic materials. Our findings reveal that while altermagnets are abundant among magnetic materials, only a tiny fraction are metallic.
Wan et al. (2025) studied this question.