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@inproceedings{483226,
author = {Muzikář, Martin and Farková, Marta and Havel, Josef},
address = {Brno},
booktitle = {CHEMOMETRICS VI},
edition = {I.},
keywords = {artificial neural networks; capillary zone electrophoresis},
language = {eng},
location = {Brno},
isbn = {80-210-2918-8},
pages = {P17},
publisher = {Masaryk University Press},
title = {SOFT MODELLING OF ELECTROPHORETIC MOBILITIES AND PREDICTION OF ANIONS RESOLUTION USING ARTIFICIAL NEURAL NETWORKS},
year = {2002}
}
TY - JOUR
ID - 483226
AU - Muzikář, Martin - Farková, Marta - Havel, Josef
PY - 2002
TI - SOFT MODELLING OF ELECTROPHORETIC MOBILITIES AND PREDICTION OF ANIONS RESOLUTION USING ARTIFICIAL NEURAL NETWORKS
PB - Masaryk University Press
CY - Brno
SN - 8021029188
KW - artificial neural networks
KW - capillary zone electrophoresis
N2 - 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.
ER -
MUZIKÁŘ, Martin, Marta FARKOVÁ a Josef HAVEL. SOFT MODELLING OF ELECTROPHORETIC MOBILITIES AND PREDICTION OF ANIONS RESOLUTION USING ARTIFICIAL NEURAL NETWORKS. In \textit{CHEMOMETRICS VI}. I. Brno: Masaryk University Press, 2002, s.~P17, 1 s. ISBN~80-210-2918-8.
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