ABSTRACT
BACKGROUND: Dominating David-derived networks are widely studied due to their fractal nature, with applications in topology, chemistry, and computer sciences. The use of molecular structure descriptors is a standard procedure that is used to correlate the biological activity of molecules with their chemical structures, which can be useful in the field of pharmacology. OBJECTIVE: This article's goal is to develop analytically closed computing formulas for eccentricity-based descriptors of the second type of dominating David-derived derived network. Thermodynamic characteristics, physicochemical properties, and chemical and biological activities of chemical graphs are just a few of the many properties that may be determined using these computation formulas. METHODS: Vertex sets were initially divided according to their degrees, eccentricities, and cardinalities of occurrence. The eccentricity-based indices are then computed using some combinatorics and these partitions. RESULTS: Total eccentricity, average eccentricity, and the Zagreb index are distance-based topological indices utilized in this study for the second type of dominating David-derived network, denoted as D_2 (m). CONCLUSION: These calculations will assist the readers in estimating the fractal and difficult-to-handle thermodynamic and physicochemical aspects of chemical structure. Apart from configuration and impact resistance, the D_2 (m) design has been used for fundamental reasons in a variety of technical and scientific advancements.
