Optimization of isocratic separations
Abstract Separations can be optimized by performing a large number of experiments and choosing the best result. This can be done randomly, based on unwritten understanding (intuition) and experience, based on a more rational 'try and error' approach, or based on a design (experimental design), where the settings for the experiments are determined in advance and, if possible, programmed in the LC equipment. All approaches have been and are being followed in practice and there is a substantial amount of scientific literature available, in which a large number of different ways for optimizing separations are promoted. It is not easy to find your way in this. In this section we try to show a clear route for optimizing an isocratic separation. The point here is that we want to work with simple means (not with complex computer programs) and that we want to make decisions and achieve results based on (i) knowledge established in the other chapters of this publication and (ii) logical reasoning.
This chapter has been written by Peter Schoenmakers, Stella Brudin and Peter Pruim.
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