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@inproceedings{483389,
author = {Lubal, Přemysl and Havel, Josef and Farková, Marta},
address = {Brno},
booktitle = {Book of Abstracts of International Chemometric Conference Chemometrics VI},
keywords = {artificial neural networks; metal complexes; capillary zone electrophoresis},
language = {eng},
location = {Brno},
isbn = {80-210-2918-8},
pages = {P14},
publisher = {Masaryk University Press},
title = {ANN Prediction of Migration Behaviour of Metal Complexes in Capillary Zone Electrophoresis},
year = {2002}
}
TY - JOUR
ID - 483389
AU - Lubal, Přemysl - Havel, Josef - Farková, Marta
PY - 2002
TI - ANN Prediction of Migration Behaviour of Metal Complexes in Capillary Zone Electrophoresis
PB - Masaryk University Press
CY - Brno
SN - 8021029188
KW - artificial neural networks
KW - metal complexes
KW - capillary zone electrophoresis
N2 - The knowledge of migration behaviour is important in order to find the optimal experimental conditions for analyte determination by electromigration techniques, e.g. capillary zone electrophoresis (CZE). The metal ion analysis by means of CZE was possible as a consequence of application metal complexes with various organic and inorganic ligands. The metal complexes are responsible for metal ion speciation in solution and their mobility in environment. Recently, the systematic analysis of relationships between migration parameters and charge and size characteristics of metal complexes was done [1]. This quantitative structure-mobility relationships (QSMR's) are based on a function of electrophoretic mobility using enlarged Stokes-Einstein diffusion model with structural descriptors (metal atom electronegativity or effective charge) as well as the formal charge and ligand number [1]. The migration parameters are also dependent on experimental conditions (ionic strength, temperature, etc.). In this contribution, the method of migration behaviour prediction for different metal organic and inorganic complexes using "soft" modelling with artificial neural networks (ANN's) was examined on data taken from literature [1]. The achieved results were compared with values obtained by "hard" modelling (QSMR's). The proposed methodology allows to predict migration parameters and is not dependent on applied relationship. This alternative model-free approach can be used in practice for optimisation metal ion analysis by means of CZE.
ER -
LUBAL, Přemysl, Josef HAVEL and Marta FARKOVÁ. ANN Prediction of Migration Behaviour of Metal Complexes in Capillary Zone Electrophoresis. In \textit{Book of Abstracts of International Chemometric Conference Chemometrics VI}. Brno: Masaryk University Press, 2002, p.~P14, 1 pp. ISBN~80-210-2918-8.
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