QSPR Approach to Predict the Physicochemical Properties of Polycyclic Aromatic Hydrocarbons Using Degree-Based Topological Indices

Abstract

 The persistent harmful effects of polycyclic aromatic hydrocarbons (PAH) and other organic contaminants make water pollution a major environmental concern. Comprehending their physicochemical behaviour is essential for determining their influence on the environment and directing pollution control measures. Chemical graph theory makes extensive use of topological indices (TI) to forecast the physicochemical characteristics of these organic molecules by developing a Quantitative Structure-Property Relationship (QSPR) model. This study particularly uses novel degree-based topological indices for creating mathematical relationships between chemical structures and characteristics like molecular weight, boiling point, flash point, log p, enthalpy of vaporization, molar refractivity, molar volume, and polarizability. The Correlation between physicochemical properties and topological indices are established by statistical methods. To create prediction models, regressions like linear, quadratic, cubic, logarithmic, and exponential were established. According to the findings, topological indices offer a reliable and affordable alternative to conventional experimental techniques, facilitating the quick prediction of physicochemical properties.