Residue class separation results

Theory. SIMCA is a parametric classification method introduced by Wold (29), which supposes that the objects of a given class are normally distributed. The particularity of this PCA-based method is that one model is built for each class separately, that is, disjoint class modeling is performed. The algorithm starts by determining the optimal number of PCs for each individual model with CV. The resulting PCs are then used to define a hypervolume for each class. The boundary around one group of objects is then the confidence limit for the residuals of all objects determined by a statistical T-test (30, 31). The direction of the PCs and the limits established for these PCs define the model of a class (Fig. 13.13). 

Suitable inlets commonly used for liquids or solutions can be separated into three major classes, two of which are discussed in Parts A and C (Chapters 15 and 17). The most common method of introducing the solutions uses the nebulizer/desolvation inlet discussed here. For greater detail on types and operation of nebulizers, refer to Chapter 19. Note that, for all samples that have been previously dissolved in a liquid (dissolution of sample in acid, alkali, or solvent), it is important that high-purity liquids be used if cross-contamination of sample is to be avoided. Once the liquid has been vaporized prior to introduction of residual sample into the plasma flame, any nonvolatile impurities in the liquid will have been mixed with the sample itself, and these impurities will appear in the results of analysis. The problem can be partially circumvented by use of blanks, viz., the separate examination of levels of residues left by solvents in the absence of any sample. 

---