The molecular structure of hydroxychloroquine (HCQ) used in the treatment of malaria is recently suggested for emergency used in COVID-19. The chemical compound of HCQ is produced by chemical alteration of ethylene oxide from human products, such as waxy maize starch. The molecular graph is a graph comprising of atoms called vertices and the chemical bond between molecules is called edges. A topological index is a numerical representation of a chemical structure which correlates certain physico-chemical characteristics of underlying chemical compounds besides its numerical representation. To distinguish the creation of entropy-based measures from the structure of chemical graphs, several graph properties have been utilized. For computing the structural information of chemical graphs, the graph entropies have become the information-theoretic quantities. The graph entropy measure has attracted the research community due to its potential application in discrete mathematics, biology, and chemistry. In this paper, our contribution is to explore graph entropies for molecular structure of HCQ based on novel information function, which is the number of different degree vertices along with the number of edges between various degree vertices. More precisely, we have explored the degree-based topological characteristics of hydroxyethyl starch conjugated with hydroxychloroquine (HCQ–HEC). Also, we computed entropies of this structure by making a relation of degree-based topological indices with the help of information function. Moreover, we presented the numerical and graphical comparison of the computed results.

Due to its metal-free and visible-light responsive nature, as well as attractive electrical band structure and excellent physicochemical stability, graphitic carbon nitride has become a new multidisciplinary research hot point. In the field of environmental remediation and energy applications, this interesting semiconductor conjugated polymer is regarded as a viable material for capturing clean and unlimited solar energy. We Used information entropy introduced by Shannon to measure the complexity of the underlying graph. Configuration entropy of glass-forming liquids or thermodynamic entropy of enzyme-substrate complexations are examples of thermodynamic entropy used in molecular dynamics investigations on complex chemical systems. In this article, we computed some degree-based entropies calculated from topological indices. The numerical and graphical depiction of computed results was combined with curve fitting between calculated information entropies and topological indices. The underlying framework is built on topological indices, which provide a full picture of potentially important features that could be beneficial in structural modification of (g- $C_3{N}_4$) for certain applications.

The silicon material has provoked and stimulated significant research concern to a considerable extent taking into account its marvelous mechanical, optical, and electronic properties. Naturally, silicons are semiconductors and are utilized in the formation of various materials. For example, it is used in assembling the electronic based gadgets. In this article, we have studied the 2D structure of silicon carbide Si₂C₃ − I[m, n] and Si₂C₃ − II[m, n] and then continued to discuss some degree grounded topological descriptors in association with their corresponding entropy measures. We extend this computation to the quantitative and pictorial comparisons which could be beneficial in the structure amendment for effective implementation.