A New Approach for Generalized Fractal Dimensions Based on Topological Indices for Pyracyclene and Pentahexoctite Networks
K. Yogalakshmi, D. Easwaramoorthy · IEEE Access · 2024
Self-similar molecular structures have been recently become popular due to topological indices, which are numerical parameters for network graphs. Topological indices are essential in chemical network analysis to describe the essential connectivity of complex form of molecular architectures. Degree and neighborhood degree-based topological indices have been extensively investigated and are connected to many chemical properties. We discuss the complexity of two-dimensional (2D) graphene allotropes such as Pyracyclene (PC) and Pentahexoctite (PH) networks through the Generalized Fractal Dimensions (GFD), which are newly developed by using special types of topological indices. This work explores various degree and neighborhood degree-based topological indices for these networks by employing an edge partitioning technique. Using the multifractal theory, we have calculated GFD values through several types of graph-based topological indices for these structures. To analyze the level of complexity of given structures, the obtained generalized fractal dimensions are also compared graphically and tabularly by all indices.