A team of scientists from Ames National Laboratory has developed a machine learning model that can predict the Curie temperature of new material combinations, a crucial step in designing new permanent magnet materials. These materials are essential for various technologies, but they often contain critical elements that are in high demand and limited availability. The researchers used experimental data and theoretical modeling to train their machine learning algorithm, which can save time and resources compared to traditional experimental methods. The team successfully tested the model on compounds based on earth-abundant elements, proving its potential for designing future permanent magnets.
https://phys.org/news/2023-09-ai-magnetic-materials-critical-elements.html