Investigation of the solution initial pH effects on the performance of UV/Fe-ZSM5/H(2)O(2) process.

Effect of the solution initial pH was investigated on the performance of photo-Fenton process using Fe-ZSM5 zeolite as a heterogeneous catalyst for degradation of azo dye Acid Red 14. All experiments were performed in a 1.0 L tubular closed circulation batch photo-reactor. The dye degradation quantum yield was maximal when the solution initial pH was about 5. An amount of about 0.3 mg L(-1) of Fe ions leached out of the zeolite. However, monitoring Fe ion concentration during the experiments showed that the efficiency of the process is not due to the leached Fe ions. The effect of pH on decomposition rate of hydrogen peroxide in different systems such as H(2)O(2) alone, UV/H(2)O(2), UV/Zeolite and UV/Zeolite/H(2)O(2) was explored in detail to explain the results obtained.

Oxidative treatment of azo dyes in aqueous solution by potassium permanganate.

This work was conducted to study the ability of permanganate (KMnO(4)) oxidative treatment as a method to decolourise the solutions containing azo dye C.I. Acid Orange 7, C.I. Acid Orange 8, C.I. Acid Red 14, or C.I. Acid Red 73, in a batch system. The results of the study demonstrated the complete removal of the colour and partial mineralization for each dye solution. The effect of the key operating variables such as initial dye concentration, permanganate amount, pH and temperature were studied. Decolourisation reactions were influenced by the acidity and temperature of the treated solutions. To avoid the overdose of KMnO(4), the stoichiometric amount of permanganate required for 1 mol of dye complete colour removal was determined. The reactions between permanganate and C.I. Acid Orange 7, C.I. Acid Orange 8, C.I. Acid Red 14 and C.I. Acid Red 73 dyes in acidic medium exhibit (2.05, 2.20, 2.42 and 2.79):1 stoichiometry (MnO(4)(-):dye). Dye degradation efficiency by potassium permanganate was studied, monitoring total organic carbon (TOC). The results indicated that the degradation efficiency of azo dyes increased with the increase of the potassium permanganate amount. Meanwhile, even in large excess of the oxidant, the dye mineralization was incomplete.

The evaluation of electrical energy per order (E(Eo)) for photooxidative decolorization of four textile dye solutions by the kinetic model.

Photooxidative decolorization of four textile dyestuffs, C.I. Acid Orange 7 (AO7), C.I. Acid Orange 8 (AO8), C.I. Acid Orange 52 (AO52) and C.I. Acid Blue 74 (AB74), by UV/H2O2 was investigated in a laboratory scale photoreactor equipped with a 15 W low pressure mercury vapour lamp. The decolorization of the dyes was found to follow pseudo-first-order kinetics, and hence the figure-of-merit electrical energy per order (E(Eo)) is appropriate for estimating the electrical energy efficiency. The E(Eo) values were found to depend on the concentration of H2O2, concentration and basic structure of the dye. This study shows that these textile dyes can be treated easily and effectively with the UV/H2O2 process with E(Eo) values between 0.4 and 5 kW h m-3 order-1, depending on the initial concentrations of dyes and H2O2. The kinetic model, based on the initial rates of degradation, provided good prediction of the E(Eo) values for a variety of conditions.

Near melting point flow injection: a drastic enhancement in FAAS detection limits.

The described technique is based on segregation phenomena taking place in solids near their melting point. High impurity concentration occurs in a liquid phase at the grain boundaries. A continuous flow of an adequate solvent is used in far from equilibrium conditions to reach high extraction efficiency of the analyte. As an example, the determination of trace amounts of caesium in metallic sodium is described. The 5 mg/kg detection limit of conventional FAAS is thus lowered to a few microg/kg.

Modeling and optimization of heterogeneous photo-Fenton process with response surface methodology and artificial neural networks.

In this study, estimation capacities of response surface methodology (RSM) and artificial neural network (ANN) in a heterogeneous photo-Fenton process were investigated. The zeolite Fe-ZSM5 was used as heterogeneous catalyst of the process for degradation of C.I. Acid Red 14 azo dye. The efficiency of the process was studied as a function of four independent variables, concentration of the catalyst, molar ratio of initial concentration of H2O2 to that of the dye (H value), initial concentration of the dye and initial pH of the solution. First, a central composite design (CCD) and response surface methodology were used to evaluate simple and combined effects of these parameters and to optimize process efficiency. Satisfactory prediction second-order regression was derived by RSM. Then, the independent parameters were fed as inputs to an artificial neural network while the output of the network was the degradation efficiency of the process. The multilayer feed-forward networks were trained by the sets of input-output patterns using a backpropagation algorithm. Comparable results were achieved for data fitting by using ANN and RSM. In both methods, the dye mineralization process was mainly influenced by pH and the initial concentration of the dye, whereas the other factors showed lower effects.