
Use and Limits of Scouting Experiments for Retention Modelling
We all know gradient data is less reliable than isocratic data for modelling retention. But to what extend? We investigated this together with the group of Dwight Stoll.
Welcome to the website of the Chemometrics & Advanced Separations Team (CAST) of the University of Amsterdam and VU Amsterdam University. The team comprises enthusiastic researchers from both universities who devote a bit of their time to developing guides and tools for use by the community. Here, you will be able to find useful, information, software and tools for use in multi-dimensional chromatography.
We all know gradient data is less reliable than isocratic data for modelling retention. But to what extend? We investigated this together with the group of Dwight Stoll.
Tijmen Bos and other CAST members collaborated with Agilent Technologies to investigate means to minimize the effect of gradient deformation to retention modelling in LC.
Every other year, the combined analytical chemistry groups of the University of Amsterdam and VU University Amsterdam organize the International Symposium on the Separation and
PhD candidate Mimi den Uijl has together with her co-workers reviewed recent applications of retention modelling in LC. In the review, den Uijl furthermore identified key application areas where retention modelling received a significant degree of interest.
What are the latest developments around detection techniques for (polymer) LC? Where are the opportunities? Our talented PhD candidate and colleague Wouter Knol answers these and more questions in his open-access review published in Journal of Separation Sciences together with polymer expert Prof. Ron Peters.
A joint study by the University of Waterloo (Prof. Tadeusz Górecki), the Stellenbosch University (Prof. Andre de Villiers) and the University of Amsterdam (Dr. Bob Pirok) was just published in Journal of Chromatography A. In the study, parallel gradients are evaluated as alternative for shifted gradients in comprehensive 2D-LC.
We maintain a searchable database containing all 2D-LC methods published since the 1978 paper by Erni and Frei. The database, which contains over 550 methods, is part of a collaboration between the University of Amsterdam (Pirok) and Gustavus Adolphus College (Stoll).