Statistical analysis of topological indices in linear phenylenes for predicting physicochemical properties using algorithms

QSPR mathematically links physicochemical properties with the structure of a molecule. The physicochemical properties of chemical molecules can be predicted using topological indices. It is an effective method for eliminating costly and time-consuming laboratory tests. We established a QSPR between mev-degree and mve-degree-based indices and the physical properties of benzenoid hydrocarbons. To compute these indices, we designed a program using Maple software and the correlation between indices and physical properties was developed using the SPSS software. Our study reveals that the mve-degree-based sum-connectivity \((\chi ^{mve})\) $({\chi }^{\mathit{mve}})$ and atom bond connectivity ( \(ABC^{mve}\) $AB{C}^{\mathit{mve}}$ ) index, mev-degree-based Randić ( \(R^{mev}\) $R^{\mathit{mev}}$ ) and Zagreb ( \(M^{mev}\) $M^{\mathit{mev}}$ ) index are the three most significant parameters and have good prediction ability for the physicochemical properties. We examined that \(R^{mev}\) $R^{\mathit{mev}}$ predicts the molar refractivity and boiling point, \({\chi }^{mve}\) ${\chi }^{\mathit{mve}}$ predicts the LogP and enthalpy, \(ABC^{mve}\) $AB{C}^{\mathit{mve}}$ predicts the molecular weight, \(M^{mev}\) $M^{\mathit{mev}}$ predicts the Gibb’s energy, Pie-electron energy and Henry’s law. Moreover, we computed the indices for the linear [n]-phenylen.