On physical analysis of topological indices and entropy measures for porphyrazine structure using logarithmic regression model

Abstract

Abstract The porphyrazine structure, known for its high chemical and thermal stability, has become a significant focus in materials science, chemical reactivity, functionalization, and drug design. By utilizing the new Zagreb-type indices to analyze the chemical structure of porphyrazine, we can gather more information about their bonding and connecting patterns. This enables us to construct an entropy measure that helps evaluate the stability of the material and predict its behavior in different scenarios. Furthermore, establishing correlations between these indices and entropy using logarithmic regression models allows for a deeper understanding of complex properties of porphyrazine. This, in turn, opens up new possibilities for the compound’s potential applications across various scientific and technical fields. In our work, we have used the M-polynomial to derive molecular descriptors for degree-based topological indices and determine the entropy of the porphyrazine structure based on these descriptors.

Keywords

• Regression analysis
• Logarithmic regression
• M-polynomial
• Porphyrazine structure
• Topological indices
• Graph entropy