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Statistical theory, component overlap

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. [Pg.22]

Davis, J.M., Giddings, J.C. (1983). Statistical theory of component overlap in multicomponent chromatograms. Anal. Chem. 55, 418-424. [Pg.31]

Statistical Theory of Component Overlap in Multicomponent Chromatograms, J. M. Davis and J. C. Giddings, Anal. Chem., 55, 418 (1983). [Pg.300]

With V— 102-5 x 104 and z = 1-10, as above, we see that from 10 to 800 distinct peaks can theoretically be resolved in electrophoresis. (In practice the number of resolvable components is much less than nc due to statistical peak overlap as explained in Section 6.7). This enormous resolving power is consistent with observation (see Figures 8.2 and 8.4). Theory thus provides an explanation of the unusual power of electrophoresis and an insight into the variables (z and V) that must be manipulated for increased performance. [Pg.166]


See other pages where Statistical theory, component overlap is mentioned: [Pg.130]    [Pg.21]    [Pg.9]    [Pg.58]    [Pg.679]    [Pg.39]    [Pg.97]    [Pg.59]    [Pg.59]    [Pg.1860]   
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