Linear solvation energy relationships LSER

Much effort has been devoted to the development of reliable calculation methods for the prediction of the retention behaviour of analyses with well-known chemical structure and physicochemical parameters. Calculations can facilitate the rapid optimization of the separation process, reducing the number of preliminary experiments required for optimization. It has been earlier recognized that only one physicochemical parameter is not sufficient for the prediction of the retention of analyte in any RP-HPLC system. One of the most popular multivariate models for the calculation of the retention parameters of analyte is the linear solvation energy relationship (LSER) ... 

The LFER, which is also known as the linear solvation-energy relationship (LSER), was developed by Taft et al. (62) and established by Abraham and coworkers (63). The LFER has been used for characterization of two-phase partitioning processes of solutes such as octanol-water and chromatographic processes such as HPLC, GLC, and TLC. The general equation is expressed as follows ... 

A linear solvation energy relationship (LSER) has been developed to predict the water-supercritical CO2 partition coefficients for a published collection of data. The independent variables in the model are empirically determined descriptors of the solute and solvent molecules. The LSER approach provides an average absolute relative deviation of 22% in the prediction of the water-supercritical CO2 partition coefficients for the six solutes considered. Results suggest that other types of equilibrium processes in supercritical fluids may be modeled using a LSER approach (Lagalante and Bruno, 1998). 

Let us now extend our molecular descriptor model introduced in Chapter 4 (Eqs. 4-26 and 4-27) to the aqueous activity coefficient. We should point out it is not our principal goal to derive an optimized tool for prediction of yw, but to develop further our understanding of how certain structural features determine a compound s partitioning behavior between aqueous and nonaqueous phases. Therefore, we will try to keep our model as simple as possible. For a more comprehensive treatment of this topic [i.e., of so-called linear solvation energy relationships (LSERs)] we refer to the literature (e.g., Kamlet et al., 1983 Abraham et al., 1990 Abraham, 1993 Abraham et al., 1994a and b Sherman et al., 1996). 

Since solvatochromic parameters are derived from direct measurements of the energy resulting from intermolecular interaction, they can be used to predict solubility, which is determined by solute-solute, solvent-solvent, and solute-solvent interaction energies. For nonself-associated liquid aliphatic compounds with a weak or nonhydrogen-bond donor (Taft etal., 1985 Kamlet etal., 1986), the solubility in water at 29S was related to molar volunWjf, hydrogen-bond basicity j and polarity/polarizability (jf) by a linear solvation energy relationship (LSER) as in Equation 3.55 ... 

A linear solvation energy relationship (LSER) method was developed by Abraham et al. (1994) using five "solvatochronic" parameters for 408 chemicals. This method is related to the LSER method described in Chapter 7. Obtaining the parameter values can be demanding and difficult, but is potentially powerful. 

It has been established (Kamlet and Taft 1985) that a large number of solvent effects involving a given solute and a series of solvents can be described by the general linear solvation energy relationship (LSER) ... 

A linear solvation energy relationship (LSER) study of tautomerism in aromatic Schiff bases and related azo compounds indicates that the aminoenone tautomer is always the more polar, and is specifically favoured by proton donor solvents (binding to the second lone pair of the carbonyl). Effects of aromatization and benzo fusion are also discussed.26... 

Many biochemical and toxicological properties of compounds Xt depend on solute-solvent interaction can be rationalized in terms of the linear solvation-energy relationship (LSER) (Kamlet et ah, 1981) ... 

The so-called solvatochromic or linear solvation energy relationship (LSER) descriptors developed by Abraham and coworkers (Kamlet et al., 1983) have proved valuable in correlating a wide variety of biological endpoints and physicochemical properties, and two studies have utilized them to model BCF. Park and Lee (1993) found the following QSAR for the fish BCF values of a set of diverse chemicals ... 

The standard molar Gibbs energy of solvation can also be derived from pure component data using spectroscopic information for determining solvatochromic parameters in respect of activity, basicity, polarity, etc. There exists a number of linear solvatochromic scales, the most widely used of which is the linear solvation energy relationship (LSER) devised by Kamlet and Taft [37, 38]. The Nernst distribution of solute i according to Kamlet is ... 

Another objective of this chapter is to explain how LFER fits in with respect to linear solvation energy relationships (LSER), quantitative structure-activity relationships (QSAR), and quantitative structure-property relationships (QSPR). Often, these methods are operationally quite similar. Their connection is addressed in the Background section. 

Linear solvation energy relationships (LSERs) have been used successfully to characterize solubility properties in a number of diverse systems, including gas/liquid chromatography (GLC), gas/solid chromatogr y (GSC), and liquid chromatography (LC) [176-179c], These relationships take the form of a multivariate linear regression, such as... 

Another important treatment of multiple interacting solvent effects, in principle analogous to Eq. (7-50) but more precisely elaborated and more generally applicable, has been proposed by Kamlet, Abboud, and Taft (KAT) [84a, 224, 226], Theirs and Koppel and Palm s approaches have much in common, i.e. that it is necessary to consider non-specific and specific solute/solvent interactions separately, and that the latter should be subdivided into solvent Lewis-acidity interactions (HBA solute/HBD solvent) and solvent Lewis-basicity interactions (HBD solute/HBA solvent). Using the solvato-chromic solvent parameters a, and n, which have already been introduced in Section 7.4 cf. Table 7-4), the multiparameter equation (7-53) has been proposed for use in so-called linear solvation energy relationships (LSER). 

Eq. (7-53) has been used in the correlation analysis by multiple regression of numerous reaction rates and equilibria, spectroscopic data, and various other solvent-dependent processes. An impressive series of 46 articles entitled Linear Solvation Energy Relationships (LSER) has been published Part 1 [229]... Part 46 [230] see also the summarizing articles [127, 224, 227] and the critical compilation of solvent parameters e.g. n and P) by Abboud and Notario [295]. 

Finally, a multiparameter correlation equation based solely on theoretically determined solvent descriptors, introduced by Famini and Wilson, deserves attention [350], Linear solvation energy relationships (LSERs), such as the KAT equation (7-54) and its successors, can be summarized by the general form shown in Eq. (7-66) ... 

Abraham and Roses [53] expressed the chromatographic relation in the general form called linear solvation energy relationships (LSER) ... 

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). 

A convenient point of departure is that of the increasingly popular quantitative structure activity relationships (QSAR) mentioned above [696,699,11], which derive adsorbate-adsorbent interaction indices from, for example, water solubility data, molecular connectivities [697], n-octanol-water partition coefficients, reversed-phase liquid chromatography capacity factors [723], or linear solvation energy relationships (LSER). 

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