Decoding ID and 2D Multicomponent Separations by Using the SMO Poisson Statistics

3 DECODING ID AND 2D MULTICOMPONENT SEPARATIONS BY USING THE SMO POISSON STATISTICS 

In order to explain this, we need to recall some basic separation parameters. The resolution between two SC peaks of the same height is defined as 

FIGURE 4.5 Clustering in ID separations, (a) Resolution between adjacent SCs defines the critical distance Axo. (b) interdistances between adjacent SCs (fourth through seventh SC) are considered. I Ax0, II Ax0, and III Ax0. Thus fifth and sixth SC are merged in the same band (doublet) that is completely separated from the previous and subsequent bands. 

Not all of the above-described statistical quantities are chromatographically observable. For example, s, d, t, and m are not directly observable unless selective detectors as a mass spectrometer is employed (Campostrini et al., 2005) and thus they are hidden quantities. The point will be discussed in the third section of this chapter. 

Peaks and their number are instead currently detected and measured by an integrator or scanning devices and thus are instead observable quantities. The main drawback is that they are evaluated on the basis of established threshold and resolution criteria that very often are not precise. Nonetheless, the response values, even if poorly defined, can be used to estimate m—a hidden quantity, see above—in a random retention pattern, as described below. 

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