Nada Glumac

Surfactants are used in various washing applications with potential negative environmental and health impacts. The ion-pair 1,3-dioctadecyl-1H-1,2,3-triazol-3-ium-tetraphenylborate (DODTA–TPB) was used to fabricate the potentiometric sensor for the quantification of anionic surfactants. The computational analysis of the DODTA⁺–TPB⁻ adduct reveals a dynamic, thermodynamically favorable interaction driven primarily by hydrophobic C–H∙∙∙π contacts and the flexibility of the C-18 chains, rather than electrostatic or π–π stacking forces. These findings, supported by the MM-PBSA, RDF, and structural analyses, align with broader trends in molecular recognition and provide a foundation for designing advanced ion-pair-based sensors. The sensor showed advanced analytical properties to anionic surfactants with low interfering effects of selected anions. The response of the SDS was investigated in the range from 8.1 × 10⁻⁸ M to 1.0 × 10⁻² M, with a slope of −59.2 mV and a limit of detection (LOD) of 3.1 × 10⁻⁷ M; and DBS was in the range of 8.1 × 10⁻⁸ M to 2.5 × 10⁻³ M with a slope of −57.5 mV and an LOD of 5.9 × 10⁻⁷ M. The sensor was tested on potential interfering ions. Potentiometric titrations of technical-grade anionic surfactants had high recovery rates from 100.2 to 100.4%. The recovery test for spiked samples of surface waters was from 94.2 to 96.5%. The sensor was tested on commercial samples containing anionic surfactants, and the results were compared and showed a good agreement with the two-phase titration method.

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.

Water is an important factor in human health and an essential ingredient of living organisms. The increase in population and living standards has led to increased water consumption, consequently causing an increase in wastewater, as well as greater quality impairment. Wastewater treatment of the public mixed drainage system of the city of Čakovec (Croatia) and surrounding suburban settlements is carried out by mechanical and biological procedures, with the final treatment of separated sludge. In this paper, we analyzed the input and output values of annual time series for chemical oxygen demand (COD) on the wastewater treatment plant in 2015 using the RAPS method (Rescaled Adjusted Partial Sums). The results showed that the input series contained more pronounced subseries with respect to their mean values and trends of increase and decrease, respectively. When comparing the input and output subseries, the output subseries does not oscillate to a large extent given that they express the output quality of wastewater. A significant reduction in the output values of the indicators determines the quality treatment of incoming wastewater.