An era of rapid evolution of structures and devices driven by new capabilities in machine learning, nanoscale experiments, and economic modeling is unfolding, MIT materials researchers revealed during the annual Industrial Liaison Program (ILP) Research and Development Conference.
Pointing to progress in areas as diverse as biomedical devices, computing, and energy, Carl Thompson, director of the MIT Materials Research Laboratory and the Stavros Salapatas Professor of Materials Science and Engineering, noted the convergence of advances in nanoscale imaging and computerized prediction of materials structure and behavior with analysis of the likelihood of success in the marketplace.
A longstanding problem with green energy sources, including solar and wind, is their power production varies widely and is often mismatched to demand. Thompson noted the work of Jessika Trancik, an associate professor of energy studies who has identified the economic value of various energy storage methods based on their relative costs. These methods include compressed air, pumped water, and vanadium-based flow batteries, in addition to traditional cell-type batteries such as nickel-cadmium, lithium ion and sodium-sulfur combinations. These insights can guide the focus of research.