Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/59228
Share/Export:
logo share SHARE logo core CORE BASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE

Invite to open peer review
Title

Background Correction and Multivariate Curve Resolution of Online Liquid Chromatography with Infrared Spectrometric Detection

AuthorsKuligowski, Julia; Quintas, Guillermo; Tauler, Romà CSIC ORCID; Lendl, Bernhard; De la Guardia, Miguel
Issue Date2011
PublisherAmerican Chemical Society
CitationAnalytical Chemistry - Columbus 83 (12) : 4855–4862 (2011)
AbstractThe use of multivariate curve resolution–alternating least-squares (MCR-ALS) in liquid chromatography–infrared detection (LC-IR) is troublesome due to the intense background absorption changes during gradient elution. Its use has been facilitated by previous removal of a significant part of the solvent background IR contributions due to common mobile phase systems employed during reversed phase gradient applications. Two straightforward background correction approaches based on simple-to-use interactive self-modeling mixture analysis (SIMPLISMA) and principal component analysis (PCA) are proposed and evaluated on reversed phase gradient LC-IR data sets obtained during the analysis of carbohydrate and nitrophenol mixtures. After subtraction of the calculated background signal, MCR-ALS provided improved signal-to-noise ratios, removed remaining mobile phase and background signal contributions, and resolved overlapping chromatographic peaks. The present approach tends to enable easy-to-use background correction to facilitate the use of MCR-ALS in online LC-IR, even in challenging situations when gradient conditions are employed and only poor chromatographic resolution is achieved. It, therefore, shows great potential to facilitate the full exploitation of the advantages of simultaneous quantification and identification of a vast amount of analytes employing online IR detection, making new exciting applications more accessible.
DescriptionJ.K. acknowledges the “V Segles” grant provided by the University of Valencia to carry out this study. Authors acknowledge the financial support of Ministerio de Educación y Ciencia (Projects AGL2007-64567 and CTQ2008-05719/BQU) and Conselleria d'Educació de la Generalitat Valenciana (Project PROMETEO 2010-055).
Publisher version (URL)http://dx.doi.org/10.1021/ac2004407
URIhttp://hdl.handle.net/10261/59228
DOI10.1021/ac2004407
ISSN0003-270
E-ISSN1520-6882
Appears in Collections:(IDAEA) Artículos

Show full item record

CORE Recommender

SCOPUSTM   
Citations

39
checked on Mar 6, 2024

WEB OF SCIENCETM
Citations

32
checked on Feb 15, 2024

Page view(s)

319
checked on Mar 28, 2024

Google ScholarTM

Check

Altmetric

Altmetric


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.