Researchers have discovered a novel way to perform “general inverse design” with reasonably high accuracy. This breakthrough paves the way for further development of a burgeoning and fast-moving field that could eventually enable the use of machine learning to accurately identify materials based on a desired set of user-defined properties. This could be revolutionary for materials science and have vast industrial benefits and use cases. The work was led by researchers from the Low Energy Electronic Systems (LEES) interdisciplinary research group atSingapore-MIT Alliance for Research and Technology (SMART), MIT’s research…
