SOFT MODELLING OF ELECTROPHORETIC MOBILITIES AND PREDICTION OF ANIONS RESOLUTION USING ARTIFICIAL NEURAL NETWORKS
| Authors | |
|---|---|
| Year of publication | 2002 |
| Type | Article in Proceedings |
| Conference | CHEMOMETRICS VI |
| MU Faculty or unit | |
| Citation | |
| Field | Analytic chemistry |
| Keywords | artificial neural networks; capillary zone electrophoresis |
| Description | The aim of this work was to developed a new buffer composition and to determine sulphate anions in the presence of high chloride excess. From preliminary screening experiments a buffer consisting of chromium trioxide, hexamethonium hydroxide and triethanolamine was selected. The prediction of optimal buffer composition was done by a combination of experimental design and artificial neural networks. The method developed has been succesfully applied for the determination of sulphate in mineral waters containing high chloride concentration. The methology has been also demonstrated on separation of other inorganic anions (nitrite and nitrate) and improvement of separation in the presence of a-cyclodextrin was investigated, as well. Using optimal electrolyte system we were able baseline-resolve sulphate from 1500 multiple excess of chloride in less than 170 sec. |
| Related projects: |