On Nirmala indices based entropy measures for the complex structure of ruthenium bipyridine

TL;DR

This paper investigates the use of Nirmala indices and entropy measures derived from graph theory to analyze the complex molecular structure of ruthenium bipyridine, demonstrating improved property prediction capabilities.

Contribution

It introduces a novel approach combining Nirmala indices with entropy measures to better predict molecular properties of ruthenium bipyridine.

Findings

Nirmala indices correlate with entropy measures for ruthenium bipyridine.

Entropy-based measures outperform Nirmala indices alone in property prediction.

Regression analysis confirms the predictive power of combined indices.

Abstract

A numerical parameter, known as a topological index, is employed to represent the molecular structure of a compound by considering its graph-theoretical properties. In the study of quantitative structure-activity relationships (QSAR) and quantitative structure-property relationships (QSPR), topological indices are used to predict the physicochemical properties of chemical compounds. Graph entropies have evolved as information-theoretic tools to investigate the structural information of a molecular graph. In this study, we compute the Nirmala index, the first and second inverse Nirmala index of the complex structure of ruthenium bipyridine, with the help of its M-polynomial. Furthermore, entropy measures for the complex structure of ruthenium bipyridine are computed using Shannon's entropy model. The comparison between the Nirmala indices and their associated entropy measures is presented through numerical computation. The correlation between the Nirmala indices and associated entropy measurements is then examined using a regression model. Finally, it is shown that the structural characteristics and properties of the complex structure of ruthenium bipyridine will be predicted by Nirmala indices-based entropy measures rather than the Nirmala indices.