Exploring thermodynamic stability of plutonium oxycarbide using a machine-learning scheme.

Plutonium oxycarbide plays a crucial role in the fabrication of a carbide fuel and the corrosion of plutonium. In this work, a machine-learning (ML) scheme is used to predict the thermodynamic stability of plutonium oxycarbide PuOC. The training data are generated within the framework of density-functional theory (DFT) and its Hubbard correction.