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In-silico method development and optimization of on-line comprehensive two-dimensional liquid chromatography via a shortcut model.
Tirapelle, Monica; Chia, Dian Ning; Duanmu, Fanyi; Besenhard, Maximilian O; Mazzei, Luca; Sorensen, Eva.
Afiliación
  • Tirapelle M; Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.
  • Chia DN; Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.
  • Duanmu F; Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.
  • Besenhard MO; Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.
  • Mazzei L; Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.
  • Sorensen E; Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK. Electronic address: e.sorensen@ucl.ac.uk.
J Chromatogr A ; 1721: 464818, 2024 Apr 26.
Article en En | MEDLINE | ID: mdl-38564929
ABSTRACT
Comprehensive two-dimensional liquid chromatography (LCxLC) represents a valuable alternative to conventional single column, or one-dimensional, liquid chromatography (1D-LC) for resolving multiple components in a complex mixture in a short time. However, developing LCxLC methods with trial-and-error experiments is challenging and time-consuming, which is why the technique is not dominant despite its significant potential. This work presents a novel shortcut model to in-silico predicting retention time and peak width within an RPLCxRPLC separation system (i.e., LCxLC systems that use reversed-phase columns (RPLC) in both separation dimensions). Our computationally effective model uses the hydrophobic-subtraction model (HSM) to predict retention and considers limitations due to the sample volume, undersampling and the maximum pressure drop. The shortcut model is used in a two-step strategy for sample-dependent optimization of RPLCxRPLC separation systems. In the first step, the Kendall's correlation coefficient of all possible combinations of available columns is evaluated, and the best column pair is selected accordingly. In the second step, the optimal values of design variables, flow rate, pH and sample loop volume, are obtained via multi-objective stochastic optimization. The strategy is applied to method development for the separation of 8, 12 and 16 component mixtures. It is shown that the proposed strategy provides an easy way to accelerate method development for full-comprehensive 2D-LC systems as it does not require any experimental campaign and an entire optimization run can take less than two minutes.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Cromatografía de Fase Inversa Idioma: En Revista: J Chromatogr A Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido Pais de publicación: Países Bajos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Cromatografía de Fase Inversa Idioma: En Revista: J Chromatogr A Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido Pais de publicación: Países Bajos