High-Throughput Search for Metallic Altermagnets by Embedded Dynamical Mean Field Theory.

Area of Science:

• Condensed Matter Physics
• Materials Science
• Computational Materials Science

Background:

• Altermagnets are a novel class of magnetic materials exhibiting unique spin properties.
• Discovering new altermagnets, especially metallic ones, is crucial for advancing spintronic applications.
• Conventional computational methods often struggle with accurately predicting properties of correlated materials.

Purpose of the Study:

• To develop and implement a high-fidelity, high-throughput screening (HTS) strategy for accelerated altermagnet discovery.
• To enhance the accuracy of predicting metallicity and spin splitting in magnetic materials compared to traditional DFT methods.
• To explore a large database of magnetic materials for new altermagnetic candidates.

Main Methods:

• Combined density functional theory (DFT) with embedded dynamical mean-field theory (eDMFT) for accurate electronic structure calculations.
• Developed an automated workflow incorporating prescreening and symmetry analysis for efficient material evaluation.
• Applied the HTS strategy to over 2000 magnetic materials.

Main Results:

• Identified two previously unreported metallic altermagnets: CrSe and CaFe4Al8.
• Confirmed one known altermagnet, CrSb, and discovered a dozen semiconducting altermagnets.
• Found that while altermagnets are common, metallic altermagnets constitute a small fraction of magnetic materials.

Conclusions:

• The developed DFT-eDMFT HTS strategy significantly improves the accuracy and efficiency of altermagnet discovery.
• The study highlights the potential of altermagnets in materials science and spintronics.
• The findings underscore the importance of considering electron correlation effects for accurate material property prediction.