Abstract
The usefulness of a non-linear least-squares type algorithm such as the Microsoft Excel Solver for response surface modeling of ionogenic solutes in reversed-phase liquid chromatography has been examined. The retention factors of adenosine, a typical ionogenic solute, in buffered mobile phases of different pH modified with methanol and/or acetonitrile were taken from the literature and fitted to a general 9-parameter equation using adequate initial estimates of the fitting parameters and/or ranges of these parameters estimated by a Monte Carlo technique described previously The validity of each fit was tested with a method suggested in the present communication. In addition, the physical meaning and significance of the fitted coefficients is discussed together with the standard errors calculated previously. The possibility of predicting the retention behaviour of adenosine on the basis of a limited number of data was also explored.
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