We discussed a simple method of generating features from a composition, which can be augmented with information extracted from CIF files, including but not limited to the space group number and unit cell parameters. Additional features could be extracted in the database, which is specific to how the data there is structured (in our case, we used PCD ). While these database-sourced features are not utilized in this study, they are further explored in the Supplementary document Table . Here, we aim to extract additional information that are useful for describing the structure. The goal is to combine measurable descriptors with explainable models to help reveal intuitive relationships between structure and properties. At the atomic level, the structural feature sets include information on coordination geometry, bond distances, and atomic environments. These structural features can be used either as standalone features or in combination with other compositional features to generate high-accuracy models, as demonstrated in this study.