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

利用算法对线性亚苯基化合物的拓扑指数进行统计分析,以预测其理化性质。

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

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