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

ABSTRACT

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 ( χ mve ) and atom bond connectivity ( A B C mve ) index, mev-degree-based Randic ( R mev ) and Zagreb ( M mev ) index are the three most significant parameters and have good prediction ability for the physicochemical properties. We examined that R mev predicts the molar refractivity and boiling point, χ mve predicts the LogP and enthalpy, A B C mve predicts the molecular weight, M mev predicts the Gibb's energy, Pie-electron energy and Henry's law. Moreover, we computed the indices for the linear [n]-phenylen.