Documentation scienceplus.abes.fr version Bêta
AttributsValeurs
type
Is Part Of
Subject
Title
  • Three-Dimensional Quantitative Structure−Property Relationship (3D-QSPR) Modelsfor Prediction of Thermodynamic Properties of Polychlorinated Biphenyls (PCBs): Enthalpies of Fusion and Their Application to Estimates of Enthalpies of Sublimationand Aqueous Solubilities
has manifestation of work
related by
Author
Abstract
  • Comparative Molecular Field Analysis (CoMFA) has been used to develop three-dimensional quantitativestructure−property relationship (3D-QSPR) models for the fusion enthalpy at the melting point (ΔfusHm(Tfus))of a representative set of polychlorinated biphenyls (PCBs). Various alignment schemes, such as inertial,as is, atom fit, and field fit, were used in this study to evaluate the predictive capabilities of the models. TheCoMFA models have also been derived using partial atomic charges calculated from the electrostatic potential(ESP) and Gasteiger−Marsili (GM) methods. The combination of atom fit alignment and GM charges yieldedthe greatest self-consistency (r2 = 0.955) and internal predictive ability (rcv2 = 0.783). This CoMFA modelwas used to predict ΔfusHm(Tfus) of the entire set of 209 PCB congeners, including 193 PCB congeners forwhich experimental values are unavailable. The CoMFA-predicted values, combined with previous estimationsof vaporization and sublimation enthalpies, were used to construct a thermodynamic cycle that validatedthe internal self-consistency of the predictions for these three thermodynamic properties. The CoMFA-predicted values of fusion enthalpy were also used to calculate aqueous solubilities of PCBs using MobileOrder and Disorder Theory. The agreement between calculated and experimental values of solubility at298.15 K, characterized by a standard deviation of ± 0.41 log units, demonstrates the utility of CoMFA-predicted values of fusion enthalpies to calculate aqueous solubilities of PCBs.
article type
is part of this journal



Alternative Linked Data Documents: ODE     Content Formats:       RDF       ODATA       Microdata