In the second step, we used these clusters as templates to create clusters of all the other elements. For each target element, the interatomic distances in the cluster were scaled by the ratio of the nearest neighbor distance of the target element and the template element. The nearest neighbor distances (Table ) are the bond distances in their most stable bulk form and are retrieved from the Materials Project . To identify a chemically diverse set of elements, we used least-squares regression to express the unrelaxed DFT-calculated cluster energies for each element as a linear combination of the energies of the remaining 54 elements. The residual errors for these fits provide a measure of the extent by which each element is different from the other 54 elements. We selected the 13 elements with the highest errors: B, Ba, Be, Ca, Cr, Cs, K, Li, Mg, Na, Rb, Sr, and Zn, as these are likely to have distinct ground state structures. We then used the genetic algorithm to search for low-energy structures for clusters of 10, 15, 20, 25, and 30 atoms for these 13 elements. The low-energy structures discovered by the genetic algorithm are shown in Figure , and their coordinates are provided in the supporting information. These 65 structures were used as structural templates for determining relationships between structural energies among different elements.