Overlapping chromatogram simulation

The program Ma in ALS, m forms the backbone of the ALS algorithm. It reads in the data set Data Chrom2a (p.251) which simulates an overlapping chromatogram of three components. It is the data set we used previously in Chapter 5.3.3 to demonstrate the concepts of iterative and explicit computation of the concentration profiles, based on the window information from EFA. 

As part of this study, random peak overlap was simulated by computergenerated chromatograms in which single-component peaks of random heights were distributed at random positions along the separation coordinate [39]. An example is shown in Figure 6.11. The numbers by each apparent... 

Certainly two-dimensional techniques have far greater peak capacity than onedimensional techniques. However, the two-dimensional techniques don t utilize the separation space as efficiently as one-dimensional techniques do. These theories and simulations utilized circles as the basis function for a two-dimensional zone. This was later relaxed to an elliptical zone shape for a more realistic zone shape (Davis, 2005) with better understanding of the surrounding boundary effects. In addition, Oros and Davis (1992) showed how to use the two-dimensional statistical theory of spot overlap to estimate the number of component zones in a complex two-dimensional chromatogram. 

Figure 6.11. Computer-generated chromatogram of 50 randomly spaced component peaks of random peak height (150-fold range). Although this chromatogram is not unduly crowded (a =0.5 for Rj = 0.5), overlap is ubiquitous, as shown by the numbers indicating how many component peaks are associated with each observed maximum. (Simulation courtesy of Joe M. Davis, Southern Illinois University.)...

A series of computer-simulated chromatograms has been generated to test the validity of a procedure derived from the statistical model for calculating the number of randomly distributed components when many of them are obscured by overlap. Plots of the logarithm of the peak count versus reciprocal peak capacity are used for this purposTI TRese plots are shown to provide reasonable estimates of the total number of components In the synthetic chromatograms. 

A large number of overlapping peaks Is visually discernible In these simulations, and yet the component number Is considerably less than the peak capacity. Only 105 maxima are observed In the first and 99 maxima In the second simulation. Respective losses of 55 and 61 components result If each maximum Is associated with a single component. These losses justify our earlier assertion that the total component number may be easily underestimated even from a high resolution chromatogram. 

The simulated chromatograms for 10% 2-propanol and three different concentrations of surfactant are given in Fig. 8.17, The disagreement among the positional and positional-shape criteria is due to the retention behavior of peaks 13-15. As the concentration of surfactant decreased from 0.12 to 0.10 M (Fig. 8.17a and 8.17b), the valley-to-peak ratio improved, and the overlapped fractions decreased to a lesser extent. The positional resolution however became worse. A further reduction in the concentration of CTAB decreased both the positional and positional-shape resolution (see peaks 9-10 and 13-15). 

The chromatogram and the determined integration results are imported and a simulation of the chromatogram is created. The simulation is adapted by means of visual shift. Deviation parameters determine the comparability with the original chromatogram. The report on the processed chromatogram provides an overview of the deviations of each separation method used. In addition, he receives a recommendation for which separation method he should apply for individual peaks overlapping, to obtain the least deviation. 

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