Linear solvation energy relationships theory

The available quantitative data for the tautomeric constants of 4 and 5 in various solvents [44] allow a detailed elucidation of the solvent effect seen. Using the tools of linear solvation energy relationship theory (see Chapter 11), it was possible to find the share of the open and closed enol tautomers in a given solvent At room temperature, in ethanol, the tautomeric mixture consists 38% a, 15% b, and 47% b in the case of 4, while, in conformity with observed spectral changes, no 5b is present at all. 

Correlation methods discussed include basic mathematical and numerical techniques, and approaches based on reference substances, empirical equations, nomographs, group contributions, linear solvation energy relationships, molecular connectivity indexes, and graph theory. Chemical data correlation foundations in classical, molecular, and statistical thermodynamics are introduced. 

A. Wang and P.W. Carr, Comparative study of the linear solvation energy relationship, linear solvent strength theory, and typical conditions model for retention prediction in reversed-phase liquid chromatography. J. Chromatogr.A 965 (2002) 3-23. 

The Kamlet-Taft u polarity/polarizability scale is based on a linear solvation energy relationship between the n it transition energy of the solute and the solvent polarity ( 1). The Onsager reaction field theory (11) is applicable to this type of relationship for nonpolar solvents, and successful correlations have previously been demonstrated using conventional liquid solvents ( 7 ). The Onsager theory attempts to describe the interactions between a polar solute molecule and the polarizable solvent in the cybotatic region. The theory predicts that the stabilization of the solute should be proportional to the polarizability of the solvent, which can be estimated from the index of refraction. Since carbon dioxide is a nonpolar fluid it would be expected that a linear relationship... 

Many attempts to correlate the analyte structure with its HPLC behavior have been made in the past [4-6], The Quantitative structure-retention relationships (QSRR) theory was introduced as a theoretical approach for the prediction of HPLC retention in combination with the Abraham and co-workers adaptation of the linear solvation energy relationship (LSER) theory to chromatographic retention [7,8],... 

A rational strategy in identifying structural parameters appropriate for QSRR analysis should start from the accepted theories of chromatographic separations. These structural parameters obtained. should quantify the abilities of analytes to take part in the postulated intermolecular interactions which determine chromatographic. separations. Empirical or semi-empirical structural parameters of analytes based on the solvatochromic comparison method and on the linear solvation energy relationships (LSER) belong to that categoiy of structural descriptors. 19,40). 

Lee also proposes to use the LSER (linear solvation energy relationship) concept in its full context and he identifies that the polarity parameter of LSER is related to the spreading pressure. The remaining parameters of Kamlet-Taft LSER (acid, base and solubility parameter) have already their analogue in the van Oss-Good theory (acid, base and LW contributions to the surface tension). Thus, Lee believes that the spreading pressure should be included in new developments and in a proper evaluation of the van Oss-Good approach. 

V. Ventosa, J. Llibre, J. Torras, C. Rovira and J. Veciana, Modeling of the solubilities of organic compounds in supercritical fluids using the linear solvation free energy relationship theory... 

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