Algorithms and Autonomous Discovery

More than a decade ago, Ichiro Takeuchi, professor of materials science and engineering, started applying the subfield of artificial intelligence (AI) known as machine learning (ML) to help develop new magnetic materials. At the time, ML was not widely used in materials science. "Now, it's all the rage," says Takeuchi, who also holds an appointment with the Maryland Energy Innovation Institute. Its current popularity is due in part to the deep learning revolution of 2012 and related advances in computer chip speed, data storage options, and rapid refinement of the science that drives its predictive analytics of algorithms. ML-based discovery in materials science is not just a lab exercise.