No abstract

The homolysis of peracetic acid (PAA) as a relevant source of free radicals (e.g., *OH) was studied in detail. Radicals formed as a result of chain radical reactions were detected with electron spin resonance and nuclear magnetic resonance spin trapping techniques and subsequently identified by means of the simulation-based fitting approach. The reaction mechanism, where a hydroxyl radical was a primary product of O-O bond rupture of PAA, was established with a complete assessment of relevant reaction thermochemistry. Total energy analysis of the reaction pathway was performed by electronic structure calculations (ab initio and semiempirical methods) at different levels and basis sets [e.g., HF/6-311G(d), B3LYP/6-31G(d)]. Furthermore, the heterogeneous MnO2/PAA system was tested for the elimination of a model aromatic compound, phenol from aqueous solution. An artificial neural network (ANN) was designed to associate the removal efficiency of phenol with relevant process parameters such as concentrations of both the catalyst and PAA and the reaction time. Results were used to train and test ANN to identify an optimized network structure, which represented the correlations between the operational parameters and removal efficiency of phenol.

No abstract

The growing interest in sonochemistry as a tool for environmental remediation leads to the need for process optimization. Sonochemistry is a complex process, which depends on physical parameters and also on the process conditions. Physical parameters are interrelated and therefore a systematic approach has to be taken to optimize the process. The effect of physical parameters on the destruction of seven estrogen hormones (17α-estradiol, 17β-estradiol, estriol, 17α-ethinylestradiol, 17α-dihydroequilin, estrone and equilin) is reported in this study. Artificial neural networks (ANN) was used as a tool to identify the correlations between these process parameters. ANN enabled the establishment of relationship between sonication parameters such as power density, power intensity, ultrasound amplitude, as well as the reactor design parameters. The major significance was attributed to the area-specific power density and the volume-specific power intensity. The results of this work provide a sound basis to design pilot and full-scale ultrasound treatment systems. Process optimization lead to a 5-fold decrease in energy consumption as compared to the commercially available reactors, thereby making the process attractive for field applications.

No abstract