Evaluation of separation in gradient elution ion chromatography by combining several retention models and objective functions
| Autor: | Marko Rogošić, Tomislav Bolanča, Štefica Cerjan-Stefanović, Šime Ukić, Melita Luša |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Chromatography
Artificial neural network Elution Ion chromatography Filtration and Separation Chloride Analytical Chemistry chemistry.chemical_compound Column chromatography chemistry Bromide Multilayer perceptron medicine Fluoride gradient elution ion chromatography objective function optimization retention model medicine.drug |
| Zdroj: | Journal of Separation Science. 31:705-713 |
| ISSN: | 1615-9314 1615-9306 |
| DOI: | 10.1002/jssc.200700470 |
| Popis: | In this work, three different methods for modeling of gradient retention were combined with several optimization objective functions in order to find the most appropriate combination to be applied in ion chromatography method development. The system studied was a set of seven inorganic anions (fluoride, chloride, nitrite, sulfate, bromide, nitrate, and phosphate) with a KOH eluent. The retention modeling methods tested were multilayer perceptron artificial neural network (MLP-ANN), radial-basis function artificial neural network (RBF-ANN), and retention model based on transfer of data from isocratic to gradient elution mode. It was shown that MLP retention model in combination with the objective function based on normalized retention difference product was the most adequate tool for optimization purposes. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text