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This study reports simulation and optimization of ion chromatography separations using multi-segment gradient elution. First, an analytical expression for the gradient retention factor under these complex elution profiles was derived. This allows a rapid retention time prediction calculations under different gradient conditions, during computer-assisted method development. Next, these analytical expressions were implemented in an in-house written Matlab(®) routine that searches for the optimal (multi-segment) gradient conditions, either via a four-segment grid search or via the recently proposed one-segment-per-component search, in which the slope is adjusted after the elution of each individual component. Evaluation of the retention time simulation and optimization approaches was performed on a mixture of 18 inorganic anions and different subsets with varying number of compounds. The two considered multi-segment gradient optimization searches resulted in similar proposed gradient profiles, and corresponding chromatograms. Moreover, the resultant chromatograms were clearly superior to the chromatograms obtained from the best simple linear gradient profiles, found via a fine grid search. The proposed approach is useful for automated method development in ion chromatography in which complex elution profiles are often used to increase the separation power.
Copyright © 2015 Elsevier B.V. All rights reserved.
Copyright © 2015 Elsevier B.V. All rights reserved.
Originele taal-2 | English |
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Pagina's (van-tot) | 101-109 |
Aantal pagina's | 9 |
Tijdschrift | Journal of Chromatography A |
Volume | 1381 |
Vroegere onlinedatum | 9 jan 2015 |
DOI's | |
Status | Published - 13 feb 2015 |
Vingerafdruk
Duik in de onderzoeksthema's van 'Computer-assisted multi-segment gradient optimization in ion chromatography'. Samen vormen ze een unieke vingerafdruk.Projecten
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SRP6: SRP (Zwaartepunt): exploitatie van de voordelen van de Orde in Opsluiting voor een groenere chemie
Desmet, G., Denayer, J., Denayer, J., Desmet, G. & Denayer, J.
1/11/12 → 31/10/22
Project: Fundamenteel