Structure-property modeling of physicochemical properties of fractal trigonal triphenylenoids by means of novel degree-based topological indices

Trigonal triphenylenoids (TTPs) are a fascinating class of organic molecules with unique structural and electronic properties. Their diverse applications, ranging from organic electronics to nonlinear optics, have spurred significant research interest in understanding their physicochemical behavior. Topological indices, mathematical descriptors derived from the molecular graph, offer valuable insights into the structural complexity and potential properties of TTPs. This work focuses on exploring the utility of degree-based topological indices in characterizing and predicting the properties of trigonal triphenylenoids. We systematically calculate various degree-based topological indices, for a diverse set of TTPs with varying substituents and topologies. The relationships between these indices and key physicochemical properties, such as HOMO-LUMO energy gap, thermodynamic stability, and reactivity are investigated using statistical and machine learning approaches. We identify significant correlations between specific degree-based indices and different properties, allowing for potential prediction of these properties based solely on the topological information.