Two descriptors of structural similarity -atom-centered symmetry functions (ACSFs) and the smooth overlap of atomic positions (SOAP) -were used to investigate geometric clustering of crystal structures and their clustering into superbasins based on threshold simulations. Both approaches provide a measure of structural similarity based on comparison of local atomic environments. ACSFs capture structural information from a series of radial and angular functions, which depend on neighbouring atom positions out to a cutoff radius R c . We use ACSFs grouped by element, ie. the functions are evaluated separately for all pairs (for radial functions) and triples (angular functions) of elements. The spacing and width of ACSFs is chosen as in the ANI-1 neural network force field. In the SOAP kernel, the local region of each atom is described individually is represented by a sum of Gaussians centered on all atoms within the local environment. The approach applied here to calculate the similarity between two structures based on similarity of their atomic environments is the regularized-entropy match (REMatch) kernel.