Degradation study of tris(2-butoxyethyl) phosphate with TiO 2 immobilized on aluminum meshes employing artificial neural networks.

This work presents the study of tris(2-butoxyethyl) phosphate advanced oxidation in TiO2-containing systems. Titania was immobilized on aluminum surfaces from recyclable materials and the results were compared with the suspension system. The initial concentration of photocatalyst and the oxidizing agent was optimized in a 2(3) experimental design and a kinetic study of the reactions was performed in the selected conditions. The experimental data were fitted to the pseudo-first-order model (rate constants estimated at 0.0129 +/- 0.0009 and 0.0079 +/- 0.0006 min(-1) for the systems with TiO2 in suspension and immobilized, respectively). Artificial neural networks were also employed to model the experimental data and they presented correlation coefficients superior to 0.98 in all the training operations. After five cycles of degradation, the TiO2-aluminum meshes exhibited a very low decrease in photocatalytic activity (inferior to 2%). Acute phytotoxicity assays demonstrated that the byproducts of the oxidation of TBEP molecules are less toxic than the raw samples regarding lettuce seeds. For both TiO2 systems, COD decreased considerably as a consequence of the degradation. The immobilized TiO2 system achieved similar degradation rates when compared with the suspension system.