This paper aims to compute the degree(valence)-based molecular descriptors for coronoid polycyclic aromatic hydrocarbons. The myriad types of coronoids have potential far-reaching applications in evolving fields such as nanotechnology and synthetic organic chemistry due to their superaromaticity and other extraordinary geometric and electronic properties. The degree-based connectivity descriptors, like the Randić, the sum-connectivity, the first and second Zagreb indices, and its co-indices have a strong correlation with the total π-electron energy and other properties which are significant for the synthesis of coronoid polycyclic aromatic compounds. In this article, the various degree(valence)-based topological descriptors are computed using the M-polynomial for coronoid structures with cavities that vary depending on their topology, which will benefit future researchers in exploring and synthesizing new coronoid structures. The analytical expressions for recently developed molecular descriptors are also derived. The degree-based indices have not been studied earlier for coronoid structures, which contributes substantial weightage to this research work. Additionally, the computed degree-based indices are compared both graphically and numerically.

Topological descriptors are non-empirical numerical quantities that describe molecular structures. These descriptors are fundamental to the QSAR/QSPR techniques that lay the groundwork for theoretical chemists to study and synthesize chemical structures. Entropic network measures are a class of topological descriptors with applications that range from quantitative characterization of a molecular structure to the study of certain chemical properties of molecular graphs. This paper focusses on computing analytical expressions of degree-based entropy measures for three prominent classes of polycyclic aromatic hydrocarbons with a coronene molecule at their center. The intriguing properties of these classes of compounds and their widespread availability warrant a study of their nature and properties from a structural standpoint. The numerical values of the entropy measures computed in this paper also provide an insight into the relationship between the entropy measures and the molecular structure.

A topological index (TI) is a real number that defines the relationship between a chemical structure and its properties and remains invariant under graph isomorphism. TIs defined for chemical structures are capable of predicting physical properties, chemical reactivity and biological activity. Several kinds of TIs have been defined and studied for different molecular structures. Graphene is the thinnest material known to man and is also extremely strong while being a good conductor of heat and electricity. With such unique features, graphene and its derivatives have found commercial uses and have also fascinated theoretical chemists. In this article, the neighbourhood sum degree-based M-polynomial and entropy measures have been computed for graphene, graphyne and graphdiyne structures. The proper analytical expressions for these indices are derived. The obtained results will enable theoretical chemists to study these exciting structures further from a structural perspective.

Curcumin (C₂₁H₂₀O₆) is a polyphenol found in the plant Curcuma longa. Even though it possesses many pharmacological effects, owing to its limited intestinal absorption, solubility, and oral bioavailability, it is more often used as a health supplement than as a lead chemical. The poly(amido)amine (PAMAM) dendrimer (nanostructure) is utilized to enhance the stability and targeted delivery of drugs. Recently, curcumin was conjugated with the PAMAM dendrimer and analyzed for its photostability. Further investigation into the physiochemical characteristics of different generations can facilitate curcumins’ targeted delivery for many diseases, including cancer. However, many of these conjugates’ physiochemical properties are not available in databases since they have not been explored theoretically or experimentally. In this article, QSAR/QSPR (quantitative structure–activity relationship/quantitative structure–property relationship) analysis of physiochemical properties was carried out for component structures, which produced encouraging results. Hence, 16 discrete adriatic topological indices and their associated entropy measures were evaluated to theoretically predict a few physiochemical properties of the conjugated structure. The predictions will aid the chemist in drug designing.

Benzenoid systems are a notable class of polycyclic aromatic compounds which have applications ranging from household materials to advanced fields like nanotechnology. Hence, the study of their fundamental properties, like observed bioactivities, carcinogenicity, toxicity, and other significant characteristics, have fascinated theoretical chemists for quite a long time. From this perspective, the topological descriptors of these networks, facilitate the prediction of their molecular properties through quantitative structure-activity (QSAR) and structure-property relationships (QSPR) methods. This article focusses on the computation of analytical expressions for nine degree-based topological descriptors using the M-polynomial, for three benzenoid structures: convex benzenoid system, hexabenzocoronene (HBC), and hexa-cata-hexabenzocoronene (cHBC). Besides, the expressions for a few recently developed indices are also calculated using edge-partition techniques. These derived indices are then compared graphically based on their numerical values. This analysis of degree-based descriptors for these structures can lay the groundwork for future researchers to discover and explore new benzenoids and their properties.