Predicting Thermodynamic Properties of PBXTHs with New Quantum Topological Indexes

Novel group quantitative structure-property relationship (QSPR) models on the thermodynamic properties of PBXTHs were presented, by the multiple linear regression (MLR) analysis method. Four thermodynamic properties were studied: the entropy (Sθ), the standard enthalpy of formation (ΔfHθ), the standard Gibbs energy of formation (ΔfGθ), and the relative standard Gibbs energy of formation (ΔRGθ). The results by the formula indicate that the calculated and predicted data in this study are in good agreement with those in literature and the deviation is within the experimental errors. To validate the estimation reliability for internal samples and the predictive ability for other samples, leave-one-out (LOO) cross validation (CV) and external validation were performed, and the results show that the models are satisfactory.

APPLICATIONS OF A NEW TOPOLOGICAL INDEX EDm IN SOME ALIPHATIC HYDROCARBONS

A novel index EDm based on ionicity index matrix, improved distance matrix, and branching degree matrix is used to describe the structural information of the molecule and realizes unique characterization of the molecular structures. The quantitative structure–property relationship (QSPR) models, with correlation coefficients (R) in the range of 0.99–1.00 for standard enthalpy of formation ([Formula: see text]), standard entropy ([Formula: see text]), molar volume (V m ), and molar refraction (R m ) of alkanes, alkenes, and alkynes, are subsequently developed using the index EDm. The leave-one-out (LOO) method and random sampling prediction (RSP) method demonstrate the models to be statistically significant and reliable. Compared with other published topological descriptors, the index EDm has many advantages such as zero degeneracy, better simulation, and so on. Furthermore, the models of solubility and octanol–water partition coefficient are built with satisfied results, which further manifests the superiority and wide application of this index.