Abstract
The two retention models, the linear solvent strength model (LSS) and the quadratic relationship, in addition to artificial neural network (ANN) approach, were compared in their ability to predict the retention behaviour of common cations (Li, Na, NH4, K, Mg, and Ca) in isocratic ion chromatography using the methanesulfonic acid (MSA) eluent. Over wide variations in the MSA concentration, the quadratic model shows a quite good prediction power. LSS can be used only for monovalent cations and in the proximity of the experimental design point. ANN fails to predict the retention for the data not included in the training set. To find the optimal conditions in the experimental design, the normalized resolution product as a chromatographic objective function was employed. The optimum MSA concentration in the eluent on a Dionex CS12 column was found to be 18 mM, with the total analysis time of less than 10 min.
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