Guo-Jing Li

Physics-Inspired Multi-Body Descriptors Enable Interpretable Density Prediction of Energetic Ionic Salts

Machine learning has introduced a transformative paradigm for the rapid prediction of crystal properties, circumventing the need for explicit knowledge of crystal packing structures. However, when applied to high-density organic systems such as energetic ionic salts, conventional general-purpose molecular descriptors...