This article describes a project led by Yanjie Fu from Arizona State University and Alix Schmidt from Dow, funded by a Grainger Foundation Frontiers of Engineering Grant. They are using artificial intelligence to expedite the development of new materials, such as polymers and inorganic materials, with unique properties. By employing deep machine learning and utilizing extensive historical data from material science, their approach allows for virtual modeling and testing of materials, reducing the time and resources needed for physical experimentation. This innovation aims to make material development more sustainable, efficient, and cost-effective. For more details, you can read the full article here: