Otimização de reator eletroquímico, com arranjo de eletrodos cilíndricos, destinado a remoção do corante reativo azul 5g de soluções sintéticas

Abstract

The growing concern about environmental issues has directly influenced the decision making of various industrial sectors. Textile industries have as challenging features, the large volume of effluents generated in its processes, as well as the presence of dyes in it. A treatment that has been studied is the electrochemical treatment, also called electrofloculation. This treatment consists in the generation of coagulants in situ from the oxidation of metallic electrodes. It is known that certain factors influence the efficiency of the treatment, such as the characteristics of the electrodes used. In this sense, the aim of the present study to optimize the operating conditions of an electrochemical reactor, with arrangement of cylindrical electrodes for the blue reactive dye removal 5G synthetic solutions. The choice of material for the construction of electrodes took into account the ease of handling and its availability in the market. It was decided in this way, to use rods that have been adjusted according to the existing electrochemical reactor and the desired area. For the tests was made using a central composite design (CCRD), and studied the influence of the current intensity and the hydraulic retention time in the response variable color removal. We performed a total of twelve tests being 2² factor assays, four replicates at the central point and four axial assays. This experiment allowed the generation of a second dregree model that later enabled process optimization. The best results obtained in the assays was 97.84% color removal, are used the operating conditions of current density of 3.14 A and the hydraulic retention time 22.09 min. From the completion of the F test showed the validity of model, with a coefficient of determination of 0.97. Validation tests were performed under the conditions 2,67 A current intensity and 15 min of hydraulic retention time, enabling the calculation of the implicit error in the model corresponding to 2.34%.