where the idealized lattice in this example is X FCC . Despite the continually expanding plethora of GNN vari- ants, we utilize CGCNN 25 due to its comparative simplicity and ability to construct models with low architecture complexity and a relatively small number of trainable parameters (see Supplementary Section 2 for details).