engleski

Advanced Optimization Strategies in Ion Chromatography

Optimization of compounds mixtures separation by using chromatographic technique can be made through the use of computer assisted modeling techniques. The reliability of an optimization procedure depends however on two factors. First, the description of the retention behavior for all compounds present in the mixture should be accurate enough. The retention of a compound on ion chromatographic column depends upon complex interactions between solute, stationary phase and mobile phase. The ability to describe these interactions quantitatively will allow retention behavior and resolution to be predicted. Two types of retention model can be identified namely theoretical (hard modeling) and empirical (soft modeling). Theoretical models are derived totally from theory and invariably require at least knowledge of parameters relating to the analyte, stationary phase and eluent before calculation of analyte retention factor is possible. [7-17] Empirical models are not based on theoretical explanations of the physical and chemical interactions. It only tries to find the best form of mathematical relation between controlled and measured parameters. [18-23] Main advantage of empirical modeling is accuracy and speed of the algorithms, while main disadvantaged is that there is not theoretical explanation of occurred interactions. Second, the criterion function used to measure the resolution of each chromatographic peak should be sufficiently informative and the global separation of all peaks in the chromatogram should be reduced to a single numerical value. The criteria function should quantify properly the separation degree by weighting the individual peak contributions, be sensitive to judge apparently similar peak arrangements, and unambiguously indicate to the analyst the optimal conditions offering the best separation. The problem of describing chromatographic separation by a general function has been addressed by several authors over the years and a number of optimizing criteria has been suggested. [24-30] The main objective of this study was to investigate which combination of chemometric tool and criteria function is best suited for optimization of separation in ion chromatography. Influences of eluent flow rate and concentration of eluent competing ion (OH-) on separation of seven inorganic anions (fluoride, chloride, nitrite, sulphate, bromide, nitrate, and phosphate) were investigated. Multi layered feed forward artificial neural network and multiple linear regression were used for development of retention model. Eight criteria separation functions, different in terms of mathematical formulations as well as in terms of chromatographic interpretation, were used as a basic tool for calculation for optimal conditions. Computer algorithm, developed by authors, enables external control of analysis time, regardless of criteria function used for optimization. That feature is included into algorithm to enable optimization of different types of samples without need for development of new retention model. In other words, it is possible to select short analysis time in the case of analyzing sample without matrix and with more or less same concentration of present components and longer analysis time for complex samples.

optimization strategies; ion chromatography

nije evidentirano