Seeking representations and models with greater ability to extrapolate to more complex nanostructures, we explored the use of graph-structured representations, which have recently gained prominence due to their ability to effectively capture complex relationships (edges) between entities (nodes). The simplest graph representation of a UCNP is a homogeneous graph in which each node is labeled with the identity and concentrations of a single type of dopant (e.g., Er) in a specific domain of the UCNP (e.g., the core), while edges encode interactions between dopants represented by those nodes, i.e., energy transfer processes. However, we found that GNNs utilizing these homogeneous graph representations exhibited equally poor accuracy for both ID and OOD testing (Table ).