Prediction of retention

Richter, W. A., Mitchem, J. C. Brown, D. (1970). The predictability of retentive value of dental cements. Journal of Prosthetic Dentistry, 24, 298-303. 

Havel, J., Madden, J. E., and Haddad, P. R., Prediction of retention times for anions in ion chromatography using artificial neural networks, Chromatograph-ia, 49, 481, 1999. 

Hanai, T., Tran, C., Hubert, J. (1981) An approach to the prediction of retention times in liquid chromatography../. High Resolution Chromatography Chromatography Communication (J. HRC CC) 4, 454—460. 

Unfortunately, none of the commonly used molecular probes is adequate to evaluate column-to-column variabilities [88]. The absolute prediction of retention of any compound involves the use of a rather complex equation [89,90] that necessitates the knowledge of various parameters for both the solute and the solvent [91]. The relative prediction of retention is based on the existence of a calibration line describing the linearity between log and interaction index. This second approach, although less general than the first, is simpler to use in practice, and it often gives more accurate results than the first. With a proper choice of calibration solutes, it is possible to take into account subtle mobile phase effects that cannot be included in the theoretical treatment. 

Natural extracts generally contain molecules with highly different retention characteristics which cannot be separated under isocratic conditions. The application of gradient elution is a necessity for these types of natural samples. However, the optimization of gradient elution on the base of isocratic data is cumbersome and the prediction of retention in gradient elution from isocratic data is difficult. Retention in an isocratic system can be described by a polynomial function ... 

The method has been proposed for the prediction of retention data in isocratic systems from data measured in gradient elution and vice versa [84], Similar calculation methods may be very important in the analysis of natural extracts containing pigments with highly different chemical structure and retention characteristics. The calculations make possible the rational design of optimal separation conditions with a minimal number of experimental runs. 

The linear solvent strength (LSS) model combined with QSRR calculations has been applied for the prediction of retention in gradient RP-HPLC. It was established that total dipole moment (jd), electron excess charge of the most negatively charged atom (<5Mm) and water-accessible molecular surface area (Awas) exert the highest impact on the retention ... 

T. Baczek and R. Kaliszan, Combination of linear solvent strength model and quantitative structure-retention relationships as a comprehensive procedure of approximate prediction of retention in gradient liquid chromatography. J. Chromatogr.A 962 (2002) 41-55. 

Various methods have been employed for the prediction of retention times in reversed-phase liquid chromatography. 

Prediction of Retention Times from log P in Reversed-phase Liquid Chromatography... 

The prediction of retention times in a given eluent from log P has been proposed for aromatic hydrocarbons.19 The log A values of phenols21 and nitrogen-containing compounds22 were also related to their logP, and the calculated log P was used for the qualitative analysis of urinary aromatic acids, i.e. for the identification of metabolites in urine from the differences of log P in reversed-phase liquid chromatography.23,24... 

Prediction of Retention Time of Ionic Compounds from log P and pKa... 

Prediction of Retention Times Based on van der Waals Volumes... 

The qualitative analysis of retention behaviour in liquid chromatography has now become possible. Quantitative retention-prediction is, however, still difficult the prediction of retention time and the optimization of separation conditions based on physicochemical properties have not yet been completely successful. One reason is the lack of an ideal stationary phase material. The stationary phase material has to be stable as part of an instrument, and this is very difficult to achieve in normal-phase liquid chromatography because the moisture in organic solvents ages the silica gel. 

In aromatic compounds the effect of a functional group on retention may be enhanced or diminished by resonance. As illustrate in Fig. 4 the curves for monofunctional benzene derivatives exhibit a mo e or less parallel slope on the plot of log k against log eluent composition whereas the multifunctional derivatives, e.g., nitroanilines, cholestenotie, show distinctly different slopes. This demonstrates how difficult the prediction of retention behavior in adsorption chromatography is. The greater the deviation of the structure from the simple model compounds used for establishing the rules, the more difficult the prediction becomes. 

In the original adsorption models, 9 is expressed as molar fraction, but it can be substituted by volume fraction without affecting significantly the accuracy of the prediction of retention, and m are... 

In ion-pair chromatography, a great number of parameters influence the retention of a charged solute e.g., the type of solute, the type and the concentration of the pairing ion, the type and the concentration of the buffer, the mobile phase composition, etc. This makes ion-pair chromatography a versatile technique at the same time as it appears to be complicated and difficult to control. From the discussion above, it is clear that a few simple basic principles often can be used to understand the retention behavior when the experimental conditions are varied. In practical work, it may be desirable to make predictions of retentions from a limited set of retention data and without going into the more complicated theoretical models. For this purpose, an approximate equation was derived that considers most of the parameters in a simple and practically useful way. For the derivation of this simple version of the model and for a guide to its use and applicability, we refer to Ref. [8]. Here, we will only state the final equation and show one simple example of its use. 

Table 3 (73) compares the retention coefficients for synthetic peptides from various sources. To ensure comparability, the data has been standardized with respect to lysine and assigned a value of 100. The table shows that there are discrepancies between the results obtained using different chromatographic systems. Predictions of retention times should therefore be made using chromatographic systems similar to those used to calculate the retention coefficients for the amino acids. Casal et al. (75a) have made a comparative study of the prediction of the retention behavior of small peptides in several columns by using partial least squares and multiple linear regression analysis. 

Hence, stationary phases can be characterized very quickly by measuring the retention indices of the five probe solutes. On the other hand, the characterization of solutes is not so easy, for a combination of reasons. In the first place, a set of five equations with five unknowns has to be solved. In the second place, the retention indices of the solute need to be obtained on five different stationary phases with known Rohrschneider constants, as well as on squalane. Hence, six different columns are needed. Moreover, in order to obtain reproducible data, very careful experimentation is required. It is especially difficult to maintain a squalane column. In this light, the choice of squalane as a reference phase has been unfortunate. Therefore, the Rohschneider scheme has become extremely popular for the characterization of stationary phases, and not for the characterization of both phases and solutes, allowing the prediction of retention indices through equation 2.5. 

The above equation is very approximate. It involves many assumptions and approximations [311], and it is not adequate for a quantitative description or prediction of retention in LC. However, because of its simplicity, it provides us with a very elegant means to explain many of the features of modem LC in qualitative terms. 

Since the geometry and flow profile (parabolic) of FFF channels is well-defined, rather exact theoretical predictions of retention and plate height can often be made. The correlation of these experimental parameters with various physicochemical properties of component species (such as molecular weight, charge, and size) is therefore possible (11, 13). 

The derivation of these different retention equations is important in several respects. First, they allow for calculation of micelle-solute binding constants, parameters which are important in many areas of micellar kinetics or chemistry. There have been several reports in the literature demonstrating this chromatographic approach for determination of micelle - solute binding constants (1,8,104,105). More importantly, they allow for prediction of retention behavior as a function of surfactant concentration (or of pH at constant micelle concentration), provided that the micelle - solute binding constant (or solute ionization constant) is known (which can be determined spectroscopically or from kinetic studies) (1,96,102). Consequently, the theory allows the chromatographer to determine the optimum conditions required for a desired separation. 

Li, J. Prediction of internal standards in reversed-phase liquid chromatography IV correlation and prediction of retention in reversed-phase ion-pair chromatography based on linear solvation energy relationships. Anal. Chim. Acta 2004, 522, 113-126. 

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