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PUBLICATIONS

Evaluation of the Impact of Peak Description on the Quantitative Capabilities of Comprehensive Two-Dimensional Liquid Chromatography

Published

Author(s)

Benjamin Place, Mallory J. Morris, Melissa M. Phillips, Lane C. Sander, Kate Rimmer

Abstract

Comprehensive, two-dimensional liquid chromatography (LCxLC) is a powerful technique for the separation of complex mixtures. Most studies using LCxLC are focused on qualitative efforts, such as increasing peak capacity. The present study examined the use of LCxLC-UV/Vis for the separation and quantification of polycyclic aromatic hydrocarbons (PAHs). More specifically, this study evaluated the impact of different peak integration approaches on the quantitative performance of the LCxLC method. For well-resolved three-dimensional peaks, parameters such as baseline definition, base peak shape, and peak width determination did not have a significant impact on accuracy and precision. For less-resolved peaks, a dropped baseline and the summation of all slices in the peak improved the accuracy and precision of the integration methods. The computational approaches to three-dimensional peak integration are provided, including fully descriptive, select slice, and summed heights integration methods, each with its own strengths and weaknesses. Overall, the integration methods presented quantify each of the PAHs within acceptable precision and accuracy ranges and have comparable performance to that of single dimension liquid chromatography.
Citation
Journal of Chromatography A
Volume
1368
Pub Type
Journals

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DOI Link

Keywords

two-dimensional liquid chromatography, peak integration, quantitation, polycyclic aromatic hydrocarbons
Analytical chemistry

Citation

Place, B. , Morris, M. , Phillips, M. , Sander, L. and Rimmer, K. (2014), Evaluation of the Impact of Peak Description on the Quantitative Capabilities of Comprehensive Two-Dimensional Liquid Chromatography, Journal of Chromatography A, [online], https://doi.org/10.1016/j.chroma.2014.09.060 (Accessed April 23, 2024)

Created October 1, 2014, Updated October 12, 2021