Electronic absorption spectroscopy was used to measure the molecular association of copper phthalocyanine tetrasulfonate in micellar solutions, a microemulsion made with cationic surfactant, and homogeneous solvents. Analysis of absorbance versus concentration data using a multiple-aggregation model and non-linear regression analysis gave values of association constants, molar absorptivities and estimates of average aggregation number. Microemulsions and aqueous micellar solutions made with alkylammonium surfactants inhibited aggregation, probably because of interactions between the phthalocyanine sulfonate groups and the cationic surfactant head groups at interfacial surfaces. Similar aggregation behavior was observed previously in multiple-bilayer films of cationic surfactants. Water and aqueous solutions containing tetraethylammonium bromide or anionic SDS micelles provide environments facilitating extensive aggregation of Cu II PcTS 4−. The major species are dimers in water and acetonitrile/water, but the formation of higher aggregates is promoted by addition of SDS or TEAB. Aprotic organic solvents provide environments intermediate between these two extremes, giving relatively large aggregation numbers (i.e. five to seven) but smaller association constants than aqueous media not containing cationic surfactants.
Direct measurement of volatile and semivolatile halogenated organic compounds of environmental interest was carried out using arrays of conducting polymer sensors. Mathematical expressions of the sensor arrays using microscopic polymer network model is described. A classical, nonparametric, and unsupervised technique of cluster analysis was used to discriminate between polychlorinated organic phenol vapor response vectors in 2-dimensional space and to identify clusters or groups to which unknown vectors are likely to belong. The characteristic pattern for each sample was used to generate the database employed in the determination of the Euclidean distances between two given patterns and the normalized sensor response, as well as to develop a 2-dimensional mapping from a multidimensional space for quantifying the distinction of the samples. Results obtained demonstrated that conducting polymer sensor arrays can be utilized in the identification and quantitation of chlorinated organic phenols based on the differences in their Euclidean distances. The systematic differences, qualitatively defined by the Euclidean difference measurements, were most clearly visible when the nature and the function of the functional groups were considered.
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