AI streamlines search for new ceramics that generate electricity

Researchers at Pennsylvania State University have developed a machine learning model that accelerates the identification of piezoelectric ceramics, materials capable of converting mechanical energy into electricity. By analyzing vast databases of crystal structures, the AI identifies candidate materials significantly faster than traditional experimental trial-and-error methods. This development could shorten the design cycle for sensors, actuators, and energy-harvesting technologies.