Magnetic Material

Research on magnetic materials centers on discovering novel compounds with enhanced properties, such as higher operating temperatures, and improving our understanding of complex magnetic phenomena. Current efforts leverage machine learning, employing techniques like graph neural networks, convolutional neural networks, and random forests, to analyze large materials databases and predict material characteristics, accelerating the discovery and design process. These advancements are crucial for developing improved technologies across various sectors, including energy generation and storage, and electronics. The improved accuracy and efficiency of these predictive models are driving significant progress in the field.