A graph-based encoding of crystal structures where atoms are nodes and bonds are edges, with node/edge features encoding atomic properties and interatomic distances. Used as input to graph neural network models (CGCNN, MEGNet, SchNet, DimeNet) for property prediction. The choice of graph construction (cutoff radius, edge features) significantly affects model performance.