Volume 50, Issue 5

A database has been developed in MS Access™ for storage and retrieval of environmental data of surfactants in Europe, as well as general information on major surfactant monitoring programs. The database contains measured concentrations (about 2100 data points) for 8 surfactant groups collected from scientific literature and unpublished reports. The quality of the monitoring data was evaluated and scored using an approach similar to the Klimisch method for judging ecotoxicology and toxicology data. The assignments involve four “Klimisch”-like categories (reliable without restriction, reliable with restriction, not reliable, not assignable), and are based on six key features of a monitoring study, of which three features were found the most important. The proposed evaluation and scoring approach is widely applicable and can easily be applied for other environmental contaminants.

Wastewater from laundry cleaning contributes to water pollution, and the amount of detergent used needs to be reduced. In the present study, water, four types of surfactants, and their microbubble mixtures were used, and washing rates were measured in swirling flows and alternating flows. The microbubble/water mixtures (average particle diameter: 25 μm; mixed with air at 1.5 vol % in water) achieved washing rates higher than those of water alone. Furthermore, microbubbles mixed with an aqueous surfactant solution had a washing rate that depended on the ionization of the surfactant: the mixtures with microbubbles and non-ionic and anionic surfactants had a washing rate that was higher than that of aqueous non-ionic and anionic surfactant solutions without microbubbles. The surface tensions of microbubble/water mixtures and mixtures of microbubbles with non-ionic and anionic surfactants were lower than those without microbubbles. These results provide evidence of an enhanced washing effect for microbubble mixtures in laundry cleaning.

A horizontal subsurface flow constructed wetland was studied with respect to its capability to remove surface active compounds from municipal wastewater. The long-term aspect (five years) of the study is emphasized. The degradation efficiency reached 82.3 and 98.5% in the case of anionic and nonionic surfactants, respectively. All data were processed using multivariate statistical analysis. The removal efficiency of anionic surfactants depended mainly on the flow rate of the influx (multiple R 2 of 0.300). A significant effect of redox potential was observed in the case of nonionic surfactants (multiple R 2 of 0.812). No systematic decrease of the surfactant degradation efficiency was observed. The constructed wetland can serve as a suitable natural alternative to clean the wastewater generated by small communities.

Removal of heavy metals i.e. Zn 2+ and Cd 2+ from aqueous solution by adsorption onto biomass based adsorbent was investigated as a function of time and different concentrations. The sample was characterized by FTIR, EDS, BET surface area and Zeta potential technique, which was reported earlier. Adsorption kinetics of Zn 2+ and Cd 2+ was tested by first order kinetics, Elovich and parabolic diffusion kinetic equations which show that the process of adsorption is diffusion controlled process. The rate of adsorption was high at high adsorption temperature. Thermodynamic parameters like Δ H° , Δ S° and Δ G° were calculated from the kinetic data. The negative value of Gibbs free energy (Δ G °) shows the spontaneous nature of the process. Freundlich, Langmuir, Temkin isotherms and distribution coefficient were found fit to the adsorption isotherm data.

Different artificial neural networks architectures have been assayed to predict percolation temperature of AOT/ i C 8 /H 2 O microemulsions in the presence of n -alkyl acids with a chain length between 0 and 24 carbons, using a multilayer perceptron with five easy-acquired entrance variables (number of carbons, log P , length of the hydrocarbon chain, p K a and acid concentration). The evaluation of the neural networks was carried out by means of RMSE and IDP, resulting that the architecture with better results consists in five input neurons, two middle layers (with five and ten neuron respectively) and one output neuron. Results prove that Artificial Neural Networks are a useful tool elaborating models to predict percolation temperature of microemulsion systems in the presence of additives.

The compatibility of surfactants, a series of alkyl amino sulfonate containing various the length of alkyl chain (dodecyl, tetradecyl, hexadecyl and octadecyl, developed in our laboratory), with formation water matching the Xinjiang Oil Field reservoir water and the dynamic interfacial tensions (DIT) behaviors between the crude oil and the formation water for a number of alkaline flooding systems were measured. These surfactants are found to be well compatible with formation water up to 0.10 g L −1 surfactant concentration, especially Dodec-AS and Tetradec-AS show a good compatibility with formation water over the full range of surfactant concentration investigated (0.01–0.20 g L −1 ). All surfactants exhibit the dynamic interfacial tension behavior, and can reach and maintain low interfacial tension at very low concentration. The time for reaching the equilibrium DIT (DIT eq ) is longer for surfactant with stronger lipophilicity, e.g. octadecyl-AS. It is interestingly found that the ratio value between DIT eq and the tension at crude oil/reservoir water interface in the absence of surfactant is in the range of 10 −4 –10 −3 mN m −1 , accordingly based on which and the previous results, four surfactants individually or with other additives together may become potent candidates for enhanced oil recovery. Fortunately, the alkyl amino sulfonate combinational systems without alkali designed by our group can reduce the interfacial tension even to 10 −4 mN m −1 at very low surfactant concentration. These surfactants or their systems have characteristic of “Green”, in addition to the excellent salt-tolerance and the less expensive cost for enhanced oil recovery, and therefore they are good oil-displacing reagents for enhanced oil recovery.

The clouding behavior of amphiphilic drug clomipramine hydrochloride (CLP) in presence of different additives like bile salts, hydrotropes (anionic, cationic and nonionic), fatty acids, sugars and cyclodextrin has been investigated. These additives are commonly used as drug delivery systems. The additives like anionic hydrotropes, bile salts and fatty acid salts increase the cloud point ( CP ) of CLP, when added in low concentrations, whereas at high concentration, decrease it. Cationic and nonionic hydrotropes increase the CP of CLP at all concentrations. All sugars decreased the CP because of their water structure making property. β-cyclodextrin behaves like simple sugar and decreases the CP of the drug solutions. The thermodynamic parameters are also evaluated: where Δ G c° is found to be negative and Δ H c° and T Δ S c° values are negative as well as positive depending upon type and nature of additive.

A series of cationic Ester-containing Gemini surfactants, alkanediyl-α- and ω-bis(dimethyl acyloxyethylammonium bromide), were synthesized and symbolized as II-m-n (m = 12; n = 3, 4, 6). The surfactants were characterized by 1 H-NMR. The surface active properties and thermodynamic properties of these surfactants at different temperatures were studied by the measurement of surface tension and electric conductivity. The esterquat Geminis surfactants of this work were found to have strong formation capacity of micellization, and the critical micelle concentration (CMC) of these surfactants are about 2.63 × 10 −4 to 4.17 × 10 −4 mol L −1 , which is one order of magnitude smaller than that of the corresponding esterquat monomer. The Gibbs free energy of surface adsorption (Δ G ad 0 ) and micellization (Δ G m 0 ) are all negative (−74.73 kJ mol −1 to −82.11 kJ mol −1 and −42.87 kJ mol −1 to −49.38 kJ mol −1 ). The thermodynamic parameters of these surfactants indicate that the surface adsorption and micellization are all enthalpy driven.