Modelling of cations retention in ion chromatography with methanesulfonic acid as eluent
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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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References
T. Bolanča, Š. Cerjan-Stefanović, M. Regelja, H. Regelja, S. Lončarić, Development of an inorganic cations ret-ention model in ion chromatography by means of arti-ficial neural networks with different two–phase training algorithms, J. Chromatogr. A 1085 (2005) 74–85.
P. Hajos, E. Szikszay, Histidine as a dipolar eluent com-ponent in cation chromatography: II. Prediction of ret-ention data for alkaline and alkaline-earth ions, J. Chromatogr., A 920 (2001) 23–30.
J.E. Madden, N. Avdalovic, P.E. Jackson, P.R. Haddad, Critical comparison of retention models for optimisation of the separation of anions in ion chromatography: III. Anion chromatography using hydroxide eluents on a Dionex AS11 stationary phase, J. Chromatogr., A 837 (1999) 65–74.
E.Y. Ordonez, J.B. Quintana, R. Rodil, R. Cela, Computer assisted optimization of liquid chromatographic separ-ations of small molecules using mixed–mode stationary phases, J. Chromatogr., A 1238 (2012) 91–104.
E. Tyteca, S.H. Park, R.A. Shellie, P.R. Haddad, G. Des-met, Computer-assisted multi-segment gradient opti-mization in ion chromatography, J. Chromatogr., A 1381 (2015) 101–109.
P. Zakaria, G. Dicinoski, M. Hanna-Brown, P.R. Haddad, Prediction of the effects of methanol and competing ion concentration on retention in the ion chromatographic separation of anionic and cationic pharmaceutically rel-ated compounds, J. Chromatogr. A 1217 (2010) 6069–
–6076.
J.E. Madden, P.R. Haddad, Critical comparison of ret-ention models for optimisation of the separation of anions in ion chromatography: I. Non-suppressed anion chromatography using phthalate eluents and three dif-ferent stationary phases, J. Chromatogr., A 829 (1998) 65–80.
J.E. Madden, P.R. Haddad, Critical comparison of retent-ion models for the optimisation of the separation of anions in ion chromatography: II. Suppressed anion chromatography using carbonate eluents, J. Chroma-togr., A 850 (1999) 29–41.
P.J. Schoenmakers, H.A.H. Billiet, L. De Galan, System-atic study of ternary solvent behaviour in reversed-phase liquid chromatography, J. Chromatogr. 218 (1981) 261–284.
P.J. Schoenmakers, H.A.H. Billiet, L. De Galan, Descript-ion of solute retention over the full range of mobile phase compositions in reversed-phase liquid chromato-graphy, J. Chromatogr. 282 (1983) 107–121.
J. Ko, J.C. Ford, Comparison of selected retention models in reversed-phase liquid chromatography, J. Chromatogr., A 913 (2001) 3–13.
S. Sremac, A. Popović, Ž. Todorović, Dj. Čokeša, A. Onjia, Interpretative optimization and artificial neural network modeling of the gas chromatographic separation of polycyclic aromatic hydrocarbons, Talanta 76 (2008) 66–
–71.
T. Bolanča, Š. Cerjan-Stefanović, M. Luša, H. Regelja, S. Lončarić, Development of gradient elution retention model in ion chromatography by using radial basis function artificial neural networks, Chemometr. Intell. Lab. 86 (2007) 95–101.
V. Drgan, M. Novič, M. Novič, Computational method for modeling of gradient separation in ion-exchange chromatography, J. Chromatogr., A 1216 (2009) 6502–
–6510.
J.E. Madden, M.J. Shaw, G.W. Dicinoski, N. Avdalovic, P.R. Haddad, Simulation and optimization of retention in ion chromatography using virtual column 2 software, Anal. Chem. 74 (2002) 6023–6030.
K. Horvath, M. Olajos, A. Felinger, P. Hajos, Retention controlling and peak shape simulation in anion chroma-tography using multiple equilibrium model and stochas-tic theory, J. Chromatogr., A 1189 (2008) 42–51.
P.F. Vanbel, B.L. Tilquin, P.J. Schoenmakers, Criteria for optimizing the separation of target analytes in complex chromatograms, Chemometr. Intell. Lab. 35 (1996) 67–
–86.
M.A. Bezerra, R.E. Santelli, E.P. Oliveira, L.S. Villar, L.A. Escaleira, Response surface methodology (RSM) as a tool for optimization in analytical chemistry, Talanta 76 (2008) 965–977.
P.F. Vanbel, P.J. Schoenmakers, Selection of adequate optimization criteria in chromatographic separations, Anal. Bioanal. Chem. 394 (2009) 1283–1289.
V.B. Di Marco, G.G. Bombi, Mathematical functions for the representation of chromatographic peaks, J. Chromatogr., A 931 (2001) 1–30.