摘要
In LC 脳 LC the peak capacity 2Dn and the orthogonality O are often used as parameters of resolving power. Unfortunately, these parameters are not easily accessible from chromatograms. In this work we will present a novel method, based on the description as vectors of experimentally easily accessible data. This approach makes it possible to calculate separation space (peak distribution) in parallelograms and other more complex geometric patterns by describing a two dimensional area by vectors. The calculated separation space allows a comparison between several column combinations and is a useful tool in optimization of LC 脳 LC analysis.