Predictive analytics of conductance and HOMO-LUMO gaps with topological descriptors of porphyrin nanosheets

Abstract

Porphyrins are planar tetrapyrolic aromatic molecules that serve as a host for the formation of metal coordination complexes, which enable additional capabilities. The 2D porphyrin derivative sheets attracted interest due to their versatility and capacity to interact with other chemicals due to the existence of a core metal ion. Topological descriptors are employed as a predictive technique to determine the physical, chemical, and structural characteristics of molecules by considering the molecular structure of compounds as molecular graphs. This paper investigates the degree and degree sum based descriptors of some potential porphyrin derivative nanosheets, using the edge partition method. We also demonstrate a predictive model for analyzing the electrical conductance of porphyrin derivative nanosheets using degree and degree sum based topological descriptors. Furthermore, the Shannon's information entropies of these porphyrin derivatives are investigated, and the HOMO-LUMO gap of these nanostructures is predicted using these entropy.