The chemometric resolution and quantification of overlapped peaks form comprehensive two-dimensional liquid chromatography

Abstract

The chemometric resolution and quantification of overlapped peaks from comprehensive two-dimensional (2D) liquid chromatography (LC × LC) data are demonstrated. The LC × LC data is produced from an in-house LC × LC analyzer that couples an anion-exchange column via a multi-port valve with a reversed-phase column connected to a UV absorbance detector. Three test mixtures, each containing a target analyte, are subjected to partial LC × LC separations to simulate likely cases of signal overlap. The resulting unresolved target-analyte signals are then analyzed by the standard-addition method and two chemometric methods. The LC × LC analyses of a test mixture and its corresponding standard-addition mixture results in two data matrices, one for each mixture. The stacking of these two data matrices produces a data structure that can then be analyzed by trilinear chemometric methods. One method, the generalized rank annihilation method (GRAM), uses a non-iterative eigenvalue-based approach to mathematically resolve overlapped trilinear signals. The other method, parallel factor analysis (PARAFAC), uses an iterative approach to resolve trilinear signals by the optimization of initial estimates using alternating least squares and signal constraints. In this paper, GRAM followed by PARAFAC analysis is shown to produce better qualitative and quantitative results than using each method separately. For instance, for all three test mixtures, the GRAM-PARAFAC approach improved quantitative accuracy by at least a factor of 4 and quantitative precision by more than 2 when compared to GRAM alone. This paper also introduces a new means of correcting run-to-run retention time shifts in comprehensive 2D chromatographic data.