Autonomous Materials Search for Magnetic Materials

In recent years, “Materials Informatics,” which leverages data science for the exploration of novel materials, has gained significant attention. Among various approaches, “autonomous materials discovery,” which integrates robotics and materials simulations with machine learning, has emerged as a promising method for efficiently navigating vast material spaces. In this study, we employed a simulation-based autonomous materials discovery approach that combines first-principles calculations with Bayesian optimization to explore a broad space of magnetic alloys. As a result, we successfully discovered and synthesized novel alloys with high magnetization.