Recent applications of retention modelling in liquid chromatography (original) (raw)
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Solvent-Dependent Regression Equations for the Prediction of Retention in Planar Chromatography
Analytical Chemistry, 1995
Both first-and second-order regression models are presented that relate retention, as the Rf of individual solutes, the log k ' of individual solutes, or the average Rf of a mixture of solutes, to the properties of the weak solvent in each of a series of 25 binary mobile phases consisting of a specified concentration of ethyl acetate as a common strong solvent. The stepwise procedure is used for constructing these models, which are for either simulated or experimental separations on silica gel. Similar regression models are used to predict separation quality, deflned by a suitable metric. A comparison of the forward and backward stepwise procedures finds that the former is the more reliable method for constructing these models. The solutes are either steroids or thep-nitrobenzyl esters of dansyl amino acids, and the sohrent descriptors are density, dipole moment, molar volume, polarizability, saturated surface area, and unsaturated surface area. The quality of regression fits obtained with models using computed dipole moment is comparable to that obtained with models using experimental (literature) dipole moment. Both nonstandardized and standardized regression models are presented. The relative contribution of each descriptor to the variability in retention may be estimated from the latter models. A set of three descriptors-dipole moment, polarizability, and saturated surface area-predicts Rffor each of the amino acid derivatives at an ethyl acetate mole fraction of 0.30. A set of two descriptors-dipole moment and saturated surface area-predicts log k ' for each of these compounds at an ethyl acetate mole firaction of 0.20. Such concordance in descriptors is not found in models predicting retention of individual steroids. Regression equations have been widely used to predict retention of solutes in both gas and liquid chromatography. The regression models are usually built using a set of potential solute descriptors such as dipole moment, polar and nonpolar surface areas, and quantum mechanical indexes. The book by Kaliszan' contains a table with 44 references to such regression models. An alternative approach that has also been very successful has + Department of Chemistry.
Journal of Chromatographic Science, 2002
The dependence on mobile phase composition of the retention of selected test analytes in different normal-and reversed-phase chromatographic systems is studied. The aim of this study is to compare the performance of six valuable retention models reported in the literature with a new empirical equation, first introduced in this study. All of these models are compared for different thin-layer chromatographic and high-performance liquid chromatographic systems by use of three criteria: the sum of the squared differences between the experimental and theoretical data, approximation of the standard deviation, and the Fisher test.
… of Chromatography A, 2004
Two-parameter equations that describe the dependence of ln k upon ϕ, where k is the retention factor and ϕ the volume fraction of the organic modifier in the mobile phase, are examined in what concerns the underlying approximations and their performance to fit experimental data obtained from reversed-phase liquid chromatography. Using 293 experimental systems, it was found that the performance of these equations to describe ln k versus ϕ data is rather low, since the percentage of the systems that can be described satisfactorily ranges from 40 to 60% depending on the fitting equation. This percentage may be raised to 75%, if the discreteness effect is properly taken into account. A further improvement to 90% of the systems studied can be achieved only by the use of three-parameter equations, which may arise by refinements of the rough approximations of the two-parameter equations. Although the refinements do not lead always to better equations, we developed a new three-parameter expression of ln k that works more satisfactorily, since it combines simplicity, linearity of its adjustable parameters and the highest applicability.
Retention models for isocratic and gradient elution in reversed-phase liquid chromatography
Journal of Chromatography A, 2009
One-and multi-variable retention models proposed for isocratic and/or gradient elution in reversed-phase liquid chromatography are critically reviewed. The thermodynamic, exo-thermodynamic or empirical arguments adopted for their derivation are presented and discussed. Their connection to the retention mechanism is also indicated and the assumptions and approximations involved in their derivation are stressed. Special attention is devoted to the fitting performance of the various models and its impact on the final predicted error between experimental and calculated retention times. The possibility of using exo-thermodynamic retention models for prediction under gradient elution is considered from a practical point of view. Finally, the use of statistical weights in the fitting procedure of a retention model and its effect on the calculated elution times as well as the transferability of retention data among isocratic and gradient elution modes are also examined and discussed.
Journal of Chromatography A, 2005
An extension of the treatment adopted in a recent paper [P. Nikitas, A. Pappa-Louisi, P. Agrafiotou, J. Chromatogr. A 946 33] was used to derive expressions describing the variation of solute retention k with composition in ternary reversed phase liquid chromatography, RP-LC, solvent systems. The equation of the partition model obtained in this way for a ternary mobile phase was identical to that previously derived using the solubility parameter concept. This equation as well as two new expressions of ln k versus organic modifiers content were tested in a variety of ternary solvent systems in order to examine the possibility of predicting retention behavior of solutes under ternary solvent mixture elution conditions from known retention characteristics in binary mobile phases. It was demonstrated the superiority of both new equations derived in this paper to that previously proposed and applied to date in ternary solvent mixtures.
Reliability of the retention factor estimations in liquid chromatography
Journal of Chromatography A, 2004
The retention factor is one of the most universally used parameters in chromatography. However, large differences in the experimental retention factor values are observed when the same compound is injected in a given stationary/mobile phase system under intermediate precision conditions. Conventional protocols for estimating retention factors have problems that mainly arise from difficulties in the holdup time measurements and the omission of the existence of extra-column times by practicing chromatographers. In the present paper, three different approaches for estimating retention factors are tested: (i) classical retention factor estimations based on the gross holdup time, (ii) based on the real holdup time (taking into account the extra-column time), and (iii) a new approach that uses 'relative' retention factors based on the use of an external standard. Assays are performed in micellar liquid chromatography (MLC) under intermediate precision conditions (different days, equipments, columns lengths, and mobile phase flow rates). The reliability of the three approaches tested is evaluated by means of precision studies, analysis of factors affecting retention factors, and uncertainty calculations. The approach based on 'relative' retention factors was found to be the most precise, reliable, and robust strategy for estimating retention factors.
Journal of Chromatography A, 2002
Six equations that express the combined effect of mobile phase pH and organic modifier content on sample retention in reversed-phase liquid chromatography (RPLC) are developed based on either the adsorption or the partition model for retention. The equations are tested against five retention data sets taken from literature. In the tests two pH scales are used, w s pH and pH. It is shown that a new seven-parameter equation works more satisfactorily, because it exhibits good numerical w s behavior, gives low values of the sum of squares of residuals and represents the experimental retention surfaces successfully. In addition, the danger of overfitting, which leads to the prediction of physically meaningless retention surfaces, is minimized by using the proposed new seven-parameter equation. Finally, the possibility of obtaining reliable pK values of weak acids or bases chromatographically by means of the derived equations is also considered and discussed.
Journal of Separation Science, 2009
A mathematical model is proposed for representing the combined effects of mobile phase solvent composition and temperature on the retention of various analytes in HPLC. The applicability of the model in describing the retention of four macrolides in aqueous mixtures of methanol and acetonitrile determined at 20-801C in various volume fractions of the organic modifiers was shown. The mean percentage deviation (MPD) was computed as an accuracy criterion in which the overall MPD of four analytes investigated in this work was 3.971.5% (N 5 72). The proposed model could be reduced to two simpler versions. The first version concerning the retention data of analytes in one organic modifier at various temperatures produced for the retention description of the above experimental system as well as for the retention of three benzodiazepines in aqueous mixtures of methanol at 25-401C an overall MPD of 3.671.8%. The more reduced version of the model for calculating the retention factor of one analyte in a given organic modifier at various temperatures produced an overall MPD of 1.771.1% for both the experimental systems studied. The accuracy of the proposed model is compared with recent models to predict the retention of an analyte with respect to solvent component of the mobile phase and the temperature of column in which the results were comparable. The main advantage of the proposed model is its capability to predict the retention of various analytes considering (i) temperature of the column, (ii) the mobile phase solvent composition, (iii) the chemical structure of the analytes and (iv) the nature of organic modifier.