Cumulative area of peaks in a multidimensional high performance liquid chromatogram

• An algorithm recognizes peaks in a 2D-separation and calculates their cumulative peak area.
• The Savitzky–Golay smoothing filter finds the derivatives of the experimental profiles.
• The shape of these derivatives informs on the number of peaks present.
• The algorithm finds the components common in adjacent cuts and the 2D-peak profile total area.
• This algorithm was validated for a series of 2D-HPLC separations of several mixtures.

An algorithm was developed to recognize peaks in a multidimensional separation and calculate their cumulative peak area. To find the retention times of peaks in a one dimensional chromatogram, the Savitzky–Golay smoothing filter was used to smooth and find the first through third derivatives of the experimental profiles. Close examination of the shape of these curves informs on the number of peaks that are present and provides starting values for fitting theoretical profiles. Due to the nature of comprehensive multidimensional HPLC, adjacent cut fractions may contain compounds common to more than one cut fraction. The algorithm determines which components were common in adjacent cuts and subsequently calculates the area of a two-dimensional peak profile by interpolating the surface of the 2D peaks between adjacent peaks. This algorithm was tested by calculating the cumulative peak area of a series of 2D-HPLC separations of alkylbenzenes, phenol and caffeine with varied concentrations. A good relationship was found between the concentration and the cumulative peak area.