AI-driven discovery of critical element-free magnetic materials by researchers

Researchers at Ames National Laboratory have developed a machine learning model that predicts the Curie temperature of new material combinations, a crucial factor in discovering critical-element-free permanent magnet materials. By training the model using experimental data and theoretical modeling, the team aims to design new magnetic materials with reduced reliance on critical materials like cobalt and rare earth elements. This approach saves time and resources compared to traditional experimentation-based methods. The successful prediction of Curie temperatures in material candidates represents an important step towards creating high-performance, sustainable permanent magnets for various technological applications.