University of KashanIranian Journal of Mathematical Chemistry2228-648914420231201On Nirmala Indices-based Entropy Measures of Silicon Carbide Network27128811412210.22052/ijmc.2023.252742.1704ENVirendra KumarDepartment of Mathematics, Institute of Science, Banaras Hindu University, Varanasi-221005, Uttar Pradesh,
India.0000-0003-0393-4979Shibsankar DasDepartment of Mathematics, Institute of Science, Banaras Hindu University, Varanasi-221005, Uttar Pradesh,
India.0000-0003-0082-6673Journal Article20230331Topological indices are numerical parameters for understanding the fundamental topology of chemical structures that correlate with the quantitative structure-property relationship (QSPR) / quantitative structure-activity relationship (QSAR) of chemical compounds. The M-polynomial is a modern mathematical approach to finding the degree-based topological indices of molecular graphs.<br />Several graph assets have been employed to discriminate the construction of entropy measures from the molecular graph of a chemical compound. Graph entropies have evolved as information-theoretic tools to investigate the structural information of a molecular graph. The possible applications of graph entropy measures in chemistry, biology and discrete mathematics have drawn the attention of researchers. In this research work, we compute the Nirmala index, first and second inverse Nirmala index for silicon carbide network $Si_{2}C_{3}\textit{-I}[p,q]$ with the help of its M-polynomial. Further, we introduce the concept of Nirmala indices-based entropy measure and enumerate them for the above-said network. Additionally, the comparison and correlation between the Nirmala indices and their associated entropy measures are presented through numerical computation and graphical approaches. Following that, curve fitting and correlation analysis are performed to investigate the relationship between the Nirmala indices and corresponding entropy measures.https://ijmc.kashanu.ac.ir/article_114122_39babab03dc25311ca588ab304fe4c89.pdf