Creating the Materials of the Future Using Machine Learning - USC Viterbi | School of Engineering

A machine learning model, called a recurrent neural network (RNN), that is being used to predict a better polymer structure with high energy storage capacity. A polymer structure is mapped into strings of characters (the white letters) and fed to the RNN model (the green gear), resulting in a list of polymer structures which likely have better energy storage capacity (the red tetrahedrons). Illustration/Chris Kim

Creating the Materials of the Future Using Machine Learning

A new M.S. degree in the Mork Family Department of Chemical Engineering and Materials Science at USC Viterbi will prepare graduates to lead the creation of advanced materials using machine learning and artificial intelligence.