6533b86efe1ef96bd12cac17

RESEARCH PRODUCT

Approaches to characterise chromatographic column performance based on global parameters accounting for peak broadening and skewness.

Juan José Baeza-baezaS. Pous-torresJose Ramon Torres-lapasioM.c. García-alvarez-coque

subject

Chromatography Reverse-PhaseChromatographyAcetonitrilesResolution (mass spectrometry)ChemistryElutionOrganic ChemistryAdrenergic beta-AntagonistsLinear modelNormal DistributionGeneral MedicineReversed-phase chromatographyBiochemistryColumn (database)Standard deviationAnalytical ChemistryNormal distributionModels ChemicalSkewnessBenzene DerivativesLinear ModelsDiuretics

description

Peak broadening and skewness are fundamental parameters in chromatography, since they affect the resolution capability of a chromatographic column. A common practice to characterise chromatographic columns is to estimate the efficiency and asymmetry factor for the peaks of one or more solutes eluted at selected experimental conditions. This has the drawback that the extra-column contributions to the peak variance and skewness make the peak shape parameters depend on the retention time. We propose and discuss here the use of several approaches that allow the estimation of global parameters (non-dependent on the retention time) to describe the column performance. The global parameters arise from different linear relationships that can be established between the peak variance, standard deviation, or half-widths with the retention time. Some of them describe exclusively the column contribution to the peak broadening, whereas others consider the extra-column effects also. The estimation of peak skewness was also possible for the approaches based on the half-widths. The proposed approaches were applied to the characterisation of different columns (Spherisorb, Zorbax SB, Zorbax Eclipse, Kromasil, Chromolith, X-Terra and Inertsil), using the chromatographic data obtained for several diuretics and basic drugs (beta-blockers).

10.1016/j.chroma.2010.02.010https://pubmed.ncbi.nlm.nih.gov/20193951