Stories, tips and updates from the world leaders in Materials Informatics.
MACHINE LEARNING AND PHYSICS-BASED MODELLING HAND-IN-HAND
Synthesizing and testing new material samples can take months and cost tens of thousands of dollars. Physics-based modelling techniques, such as Density Functional Theory (DFT) are cheaper and quicker. However, these require a large amount of computational power and can still take days. Running a machine learning model takes seconds to minutes and can predict properties over a vast design space. For this reason, AI helps scientists efficiently narrow down the number materials candidates to model and later synthesize.