RESUMO
Two new surfactant sensors were developed by synthesizing Pt-doped acid-activated multi-walled carbon nanotubes (Pt@MWCNTs). Two different ionophores using Pt@MWCNTs, a new plasticizer, and (a) cationic surfactant 1,3-dihexadecyl-1H-benzo[d]imidazol-3-ium-DHBI (Pt@MWCNT-DHBI ionophore) and (b) anionic surfactant dodecylbenzenesulfonate-DBS (Pt@MWCNT-DBS ionophore) composites were successfully synthesized and characterized. Both surfactant sensors showed a response to anionic surfactants (dodecylsulfate (SDS) and DBS) and cationic surfactants (cetylpyridinium chloride (CPC) and hexadecyltrimethylammonium bromide (CTAB)). The Pt@MWCNT-DBS sensor showed lower sensitivity than expected with the sub-Nernstian response of ≈23 mV/decade of activity for CPC and CTAB and ≈33 mV/decade of activity for SDS and DBS. The Pt@MWCNT-DHBI surfactant sensor had superior response properties, including a Nernstian response to SDS (59.1 mV/decade) and a near-Nernstian response to DBS (57.5 mV/decade), with linear response regions for both anionic surfactants down to ≈2 × 10-6 M. The Pt@MWCNT-DHBI was also useful in critical micellar concentration (CMC) detection. Common anions showed very low interferences with the sensor. The sensor was successfully employed for the potentiometric titration of a technical grade cationic surfactant with good recoveries. The content of cationic surfactants was measured in six samples of complex commercial detergents. The Pt@MWCNT-DHBI surfactant sensor showed good agreement with the ISE surfactant sensor and classical two-phase titration and could be used as an analytical tool in quality control.
RESUMO
The botanical origin of starch is of importance in industrial applications and food processing because it may influence the properties of the final product. Current microscopic methods are time-consuming. Starch consists of an origin-dependent amylose/amylopectin ratio. Triiodide ions bind characteristically to the amylose and amylopectin depending on the botanical origin of the starch. The absorbance of the starch-triiodide complex was measured for: wheat, potato, corn, rye, barley, rice, tapioca and unknown origin starch; and within the different cultivars. Each starch sample had specific parameters: starch-triiodide complex peak wavelength maximum (λ max/nm), maximum absorbance change at λ max (ΔA) and λ max shift towards the unknown origin starch sample values. The visible absorption spectra (500-800 nm) for each starch sample were used as a unique fingerprint, and then elaborated by cluster analysis. The cluster analysis managed to distinguish data of two clusters, a cereal type cluster and a potato/tapioca/rice starch cluster. The cereal subclusters extensively distinguished wheat/barley/rye starches from corn starches. Data for cultivars were mostly in good agreement within the same subclaster. The proposed method that combines cluster analysis and visible absorbance data for starch-triiodide complex was able to distinguish starch of different botanical origins and cultivars within the same species. This method is simpler and more convenient than standard time-consuming methods.