Single-component analysis methods

A method of quantitatively determining 0.2% polyvinyl acetate in polystyrene has been described by Peitscher (1979) by using difference spectroscopy. Quantitative single component analysis of polymer films has been described by Chalmers et al. (1982). All samples were prepared by hot compression molding. This treatment produces a mat film surface, which suppresses interference fringes in the IR spectrum. For quantitative analysis it is essential that the thus produced films are homogeneous, of uniform thickness, and free of bubbles and irregularities. A clear section of each was chosen for the measurements. 

The intensities of the bands in pure components and in mixtures are proportional to the concentrations of the components. The relation between measured intensities and concentration is expressed in the Lambert—Beer law (Eq. (11)). Thus it is possible to carry out quantitative investigations by methods based on band heights or preferably by methods based on integrated intensities. Both single component analysis and multicomponent analysis by multivariate methods (see Chapter 13) can be performed. 

On the other hand, techniques like Principle Component Analysis (PCA) or Partial Least Squares Regression (PLS) (see Section 9.4.6) are used for transforming the descriptor set into smaller sets with higher information density. The disadvantage of such methods is that the transformed descriptors may not be directly related to single physical effects or structural features, and the derived models are thus less interpretable. 

Analysis for Single Components The analysis of samples containing only a single electroactive analyte is straightforward. Any of the standardization methods discussed in Ghapter 5 can be used to establish the relationship between current and the concentration of analyte. 

Often, planar chromatography is used as a preparative step for the isolation of single components or classes of components for further chromatographic separation or spectroscopic elucidation. Many planar chromatographic methods have been developed for the analysis of food products, bioactive compounds from plant materials, and essential oils. 

The concept of property space, which was coined to quanhtahvely describe the phenomena in social sciences [11, 12], has found many appUcahons in computational chemistry to characterize chemical space, i.e. the range in structure and properhes covered by a large collechon of different compounds [13]. The usual methods to approach a quantitahve descriphon of chemical space is first to calculate a number of molecular descriptors for each compound and then to use multivariate analyses such as principal component analysis (PCA) to build a multidimensional hyperspace where each compound is characterized by a single set of coordinates. 

Peak purity tests are used to demonstrate that an observed chromatographic peak is attributable to a single component. Mass spectrometry is the most sensitive and accurate technique to use for peak purity evaluation because of the specific information derived from the analysis. However, a good number of HPLC methods use mobile phase conditions that are incompatible with mass spectrometry detection. In this case, PDA spectrophotometers using peak purity algorithms may be used to support the specificity of the method. Almost all commercially available diode array detectors are equipped with proprietary software that will perform these calculations. Although this technique is more universal in application to HPLC methods, the data provided is neither particularly... 

Chemometric evaluation methods can be applied to the signal from a single sensor by feeding the whole data set into an evaluation program [133,135]. Both principle component analysis (PCA) and partial least square (PLS) models were used to evaluate the data. These are chemometric methods that may be used for extracting information from a multivariate data set (e.g., from sensor arrays) [135]. The PCA analysis shows that the MISiC-FET sensor differentiates very well between different lambda values in both lean gas mixtures (excess air) and rich gas mixtures (excess fuel). The MISiC-FET sensor is seen to behave as a linear lambda sensor [133]. It... 

Analytical Methods. Many chemical and physical analysis methods exist to characterize particulate matter collected on a substrate. Though several methods are multi-species, able to quantify a number of chemical components simultaneously, no single method is sufficient to both quantify the maiorlty of the collected particulate matter mass and those components which serve to Identify and quantify source contributions. 

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