Atomistic Structures of Carbon Nanodots and Graphene Quantum Dots Generated by Monte Carlo Sampling

This dataset contains 107 atomistic geometries of carbon nanodots (CNDs) and graphene quantum dots (GQDs) investigated in the study Exploring Carbon Dot Structures: A Monte Carlo Approach by F. D'Ambrosio and E. Bodo. The structures were generated using two complementary Monte Carlo-based Python codes, MC_heavy and MC_graphene, allowing the construction of amorphous and graphene-like carbon networks with controlled nitrogen incorporation and subsequent surface functionalization. The dataset includes 92 ground-state (S₀) geometries optimized at the ωB97X-D3/def2-TZVP level and 15 excited-state (S₁) geometries optimized using TD-DFT within the Tamm–Dancoff approximation (TDA). All geometries are provided in XYZ format, together with a README and a manifest file describing their organization and composition. The dataset supports the reproducibility of the structural and optical analyses presented in the associated manuscript.