Decoration of alumina hollow fibers with zinc oxide: improvement of the photocatalytic system for methylene blue degradation.

The photocatalytic degradation of methylene blue (MB) in aqueous solutions and under visible light was investigated with dispersed and supported zinc oxide (ZnO) as catalysts. The ZnO catalyst was successfully impregnated in asymmetric alumina hollow fibers by the simple vacuum-assisted dip-coating method. According to energy-dispersive analyses, the photocatalyst was homogenously distributed in the substrate. A strong correlation was observed between the initial dye concentration and the efficiency of the supported photocatalyst. For the initial MB concentration of 5 mg L-1 and catalyst dosage of 1 g L-1, the photocatalytic system with both dispersed and supported catalysts reached almost 100% of MB degradation. The photocatalytic process followed the pseudo-first-order kinetic model, and, for the initial MB concentration of 5 mg L-1, the apparent constants were 0.05415 and 0.00642 min-1 for suspended and supported catalysts, respectively. The treated MB solutions presented low phytotoxicity to the germination Lactuca sativa seeds with germination indexes greater than 80% after irrigation with the treated MB solutions. The produced supported ZnO catalyst showed suitable photocatalytic stability even after several reuse cycles.

Comparison between Thin-Layer Models and Non-Traditional Methods in the Modelling of Drying Kinetics of Crustacean Wastes

Abstract This research aims to compare the classical thin-layer models, stepwise fit regression method (SRG) and artificial neural networks (ANN) in the modelling of drying kinetics of shrimp shell and crab exoskeleton. Thus, drying curves were obtained using a convective dryer (3.0 m/s) at temperatures of 30.45 and 60oC. The results showed a decreasing tendency for the drying time as the temperature increased for both materials. Drying curves modelling of both materials showed fitted results with R 2 adj >0.998 and MRE<13.128% for some thin-layer models. On the other hand, by SRG a simple model could be obtained as a function of time and temperature, with the greatest accuracy being found in the modelling of experimental data of crab exoskeleton, with MRE<10.149%. Finally, the ANNs were employed successfully in the modelling of drying kinetics, showing high prediction quality with the trained recurrent ANN models.