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OPTIMALIZATION OF ELSD PARAMETERS FOR HPLC CARBOHYDRATES ANALYSIS WITH AN ARTIFICIAL NEURAL NETWORK

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CRHA Tomáš PAZOUREK Jiří

Rok publikování 2023
Druh Další prezentace na konferencích
Fakulta / Pracoviště MU

Farmaceutická fakulta

Citace
Popis Evaporative light-scattering detector (ELSD) is a simple and inexpensive way to determinate analytes without a suitable chromophore. Three ‘analogue’ parameters for ELSD can be set: nebulization gas flow, temperature of an evaporator and temperature of a nebulizer. For better and faster optimalization of these parameters, a central composite (CCM) response surface design with an artificial neural network (ANN) can be used with advantage. Output of the ANN is a prediction, which gives us probably the best ELSD condition for sugars analysis. Of course, the prediction must be confirmed and verified with HPLC-ELSD measurements.

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