Predictions from Chromatographic Data

Another important factor that should be considered, when physicochemical retention coefficients are calculated from chromatographic data in MLC, is the correct subtraction of the cmc from the total concentration of surfactant. The cmc of SDS solutions decreases at low concentrations of alcohols used as modifiers, except for methanol, and increases for acetonitrile and tetrahydrofuran. When the cmc is not subtracted from the total concentration of surfactant, the errors in the calculation of the retention coefficients can be larger than 100%. However, as occurs with the dead time, for many solutes there is no significant difference between the use of total or micellar concentration of surfactant in the prediction of the retention behavior (retention factors) [11, 18],... 

The correlation between partition coefficient and chromatographic retention has been examined by many workers in an attempt to predict log F, the logarithm of water-octanol partition coefficient used in establishing structure-function relationships, from retention data or vice versa. The data (92, 203, 215) seem to imply changes in log k are linear in changes in log P but that log k changes more slowly. Some literature data suggest that the retention is directly proportional to the partition coefficient. This apparent equality disappears, however, if the data are recalculated to identical experimental conditions. 

Predictive Information from Chromatographic Retention Data... 

Excellent agreement was obtained by Fletcher el al. between the total S content of wool obtained by three methods (mean 3.65 %) and the sulfur content predicted from the analyses for cystine, cysteine, and methionine (total 3.57 %) using chromatographic data for methionine and the radioactive dilution data for (cystine S - - cysteine S). This work suggests that problems of obtaining a sulfur balance have been due partly to destruction of cystine during acid hydrolysis and partly to uncertainties in the determination of cystine in the hydrolyzates. 

The use of thermogravimetric analysis (TGA) apparatus to obtain kinetic data involves a series of trade-offs. Since we chose to employ a unit which is significantly larger than commercially available instruments (in order to obtain accurate chromatographic data), it was difficult to achieve time invariant O2 concentrations for runs with relatively rapid combustion rates. The reactor closely approximated ideal back-mixing conditions and consequently a dynamic mathematical model was used to describe the time-varying O2 concentration, temperature excursions on the shale surface and the simultaneous reaction rate. Kinetic information was extracted from the model by matching the computational predictions to the measured experimental data. 

Log P values can be measured experimentally or predicted from molecular structure. Experimental approaches run the gamut from the highly reliable and traditional shake-flask method to newer methodologies such as electrokinetic chromatographic methods that are rapid, accurate and precise, and can be automated. However, for validation purposes, partition coefficient data of large, structurally diverse datasets obtained from such systems should be compared with that from the standard octanol/water system. 

The support will affect the retention to an extent that depends on the properties of its surface and the components in the ion-pair [3, 43]. When silica based material is used as support, the deviations between the obtained capacity factors and those predicted from batch extraction data are usually significant [44, 45]. Careful thermostatting of the whole chromatographic system is a prerequisite for stable retention. 

Another even more powerful approach is the application ofthe unified equation of chromatography, which allows determining the reaction rate constants of any first-order reaction directly from chromatographic elution profiles without the need for performing reaction progress analysis. This dramatically accelerates the evaluation of temperature-dependent kinetics, as the analysis time no longer Hm-its the rate of measurements. Detailed kinetic data and activation parameters are of great importance to model and predict activities and selectivities by computational methods. 

The Prediction of Chromatographic Seiectivity from LFER Data... 

Abraham, M H Whiting, G.S. (1992). Hydrogen-bonding. Part 22. Characterization of soybean oil and prediction of activity coefficients in soybean oil from inverse gas chromatographic data. /. Am. OH Chem. Soc., 69,1236-1238. 

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