ABSTRACT
This chapter provides an overview of the mathematical models that have been reported for the description of chromatographic peak profiles. Peak profiles in chromatography are the final result of different types of interactions within the column. The accurate description of chromatographic peaks is needed to extract the relevant information of the signals for either isolated or overlapped peaks. The Gaussian function seems to be a good starting point to obtain a model that describes the deviations from the ideal behavior of chromatographic peaks. Peak asymmetry is problematic because it contributes to a loss of efficiency and favors the overlap of neighboring peaks by placing more solute in the lower area of the peak rather than around the maximum. When the peak shape is considered in the optimization process, peaks are usually assumed to be Gaussian and the column efficiency is fixed to a previously selected value.
