Semi-supervised generative approach to chemical disorder: application to point-defect formation in uranium-plutonium mixed oxides.

Chemical disorder has a major impact on the characterization of the atomic-scale properties of highly complex chemical compounds, such as the properties of point defects. Due to the vast amount of possible atomic configurations, the study of such properties becomes intractable if treated with direct sampling. In this work, we propose an alternative approach, in which samples are selected based on the local atomic composition around the defect, and the defect formation energy is obtained as a function of this local composition with a reduced computational cost.