Computational Analysis of Reverse Degree-Based Topological Indices in Hex-Derived Networks

Abstract

Topology is the mathematical study of the geometric and spatial properties that remain unchanged under continuous transformations of a graph’s shape and size. In chemical graph theory, topological indices are used to quantify various chemical properties of molecules. These indices are derived from the topological structure of a graph and are crucial in understanding the valency of a chemical substance, which is determined by the number of surrounding atoms in its molecular structure. Topological indices are connected to numerous physicochemical properties, such as vapor pressure, stability, and elastic energy. In molecular structures, topological indices provide a numerical representation of the connections between molecules. In theoretical chemistry, these indices are widely used to simulate the physicochemical characteristics of complex compounds. QSAR/QSPR studies rely heavily on topological indices to predict physical and chemical properties. This article explores the hex-derived network and its first two types, calculating reversed degree-based topological indices for these networks.