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J Chromatogr A ; 1455: 156-162, 2016 Jul 15.
Artigo em Inglês | MEDLINE | ID: mdl-27302688

RESUMO

The differential pressure drop of carrier gas by tuning the junction point pressure of a coupled column gas chromatographic system leads to a unique selectivity of the overall separation, which can be tested using a mixture of compounds with a wide range of polarity. This study demonstrates a pressure tuning (PT) GC system employing a microfluidic Deans switch located at the mid-point of the two capillary columns. This PT system allowed variations of inlet-outlet pressure differences of the two columns in a range of 52-17psi for the upstream column and 31-11psi for the downstream column. Peak shifting (differential migration) of compounds due to PT difference are related to a first order regression equation in a Plackett-Burman factorial study. Increased first (upstream) column pressure drop makes the second column characteristics more significant in the coupled column retention behavior, and conversely increased second (downstream) column pressure drop makes the first column characteristics more apparent; such variation can result in component swapping between polar and non-polar compounds. The coupled column system selectivity was evaluated in terms of linear solvation energy relationship (LSER) parameters, and their relation with different pressure drop effects has been constructed by applying multivariate principle component analysis (PCA). It has been found that the coupled column PT system descriptors provide a result that shows a clear clustering of different pressure settings, somewhat intermediate between those of the two commercial columns. This is equivalent to that obtained from a conventional single-column GC analysis where the interaction energy contributed from the stationary phases can be significantly adjusted by choice of midpoint PT. This result provides a foundation for pressure differentiation for selectivity enhancement.


Assuntos
Cromatografia Gasosa-Espectrometria de Massas , Solventes/química , Modelos Teóricos , Análise Multivariada , Pressão , Análise de Componente Principal
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