Abstract :
To improve the selectivity of surfactant sensors, the surface of their membranes was modified with molecular sieves with predetermined pore sizes. Water-soluble anionic, cationic and non-ionic surfactants were used as pore generators in the molecular sieves and introduced into the source membrane at the stage of its formation. The modified sensors enable detection of alkylsulfates homologues and alkylpyridinium with different lengths of the hydrocarbon chain (C10-C18); homologous poly(oxyethylated nonylphenols) differing in the number of oxyethyl groups (m = 10-100). A novel approach to separate detection of surfactant homologues implies the usage of inselective sensors as a multisensor system. The softwaresupported multisensor approach allows information of both mixture composition and concentrations of separate components in multicomponent systems to be obtained with a certain accuracy. Inselective non-modified sensors with the highest cross-sensitivity were used to design multisensor systems like an “electronic tongue”. The cross-sensitivity parameters of both source and modified sensors were estimated and the possibility of their usage in multisensor systems like an “electronic tongue” for analysis of multicomponent solutions of homologous surfactant is shown. Analytical signals were processed by artificial neural networks.
