Application of the advanced oxidative process on the degradation of the green leaf and purple açaí food dyes with kinetic monitoring and artificial neural network modelling.

The study evaluated the advanced oxidative processes concerning the degradation of green leaf and purple açaí dyes, as well as the prediction of data through artificial neural networks (ANNs). It was verified that percentage of degradation on the wavelengths (λ) of 215, 248, 523 and 627 nm was 5.95, 49.99, 98.17 and 95.99%, respectively, when UV/H2O2 action and UV-C radiation was applied. A non-linear kinetic model proposed by Chan and Chu presented a good fit to the experimental data, reaching an R2 value between 0.978 and 0.999, for the studied λ. Within the ANN simulations through Statistica 6.0, the multilayer perceptron (MLP) (3-9-4) presented a better fit to the experimental data. However, higher values of R² were obtained when utilizing the sklearn package with Python language and an MLP (4-5-4) model. Assays with Staphylococcus aureus and Staphylococcus pyogenes bacteria isolates were performed and it was verified that after employing the UV/H2O2 process, there was a decrease in the toxicity of the solution of dyes. In evaluating S. aureus toxicity, normal growth was observed. However, for S. pyogenes bacteria, it was found that when using the UV/H2O2 process, toxicity was evidenced at post-treatment solution concentrations of 100, 70 and 50%.

Degradation of textile dyes Remazol Yellow Gold and reactive Turquoise: optimization, toxicity and modeling by artificial neural networks.

In this work, the degradation of Remazol Yellow Gold RNL-150% and Reactive Turquoise Q-G125 were investigated using AOP: photolysis, UV/H2O2, Fenton and photo-Fenton. It was found that the photo-Fenton process employing sunlight radiation was the most efficient, obtaining percentages of degradation above 87%. The ideal conditions for the degradation of the dyes were determined from a factorial design 23 and study of the [H2O2] ([H2O2] equal to 100 mg·L-1); [Fe] equal to 1 mg·L-1 and pH between 3 and 4. In the kinetic study, a degradation of more than 97% was obtained after 150 min for the chromophoric groups and 91% for the aromatic compounds. The experimental data obtained presented a good fit to the nonlinear kinetic model. The model of artificial neural networks multilayer perceptron (MLP) (4-11-5) using the software Statistica 8.0 enabled the modeling of the degradation process and showed a better prediction of the data. The toxicity to the seeds of Lactuca sativa and the bacteria Escherichia coli and Salmonella enteritidis allowed to evaluate the effectiveness of the process. The results of this study suggest that the use of photo-Fenton process with sunlight radiation is an effective way to degrade the dyes under study.