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Abstract

A ceria loaded carbon nanotubes (CeO2/CNTs) nanocomposites photocatalyst was prepared by chemical precipitation, and the preparation conditions were optimized using an orthogonal experiment method. HR-TEM, XRD, UV-Vis/DRS, TGA and XPS were used to characterize the photocatalyst. Nitrogen adsorption-desorption was employed to determine the BET specific surface area. The results indicated that the photocatalyst has no obvious impurities. CeO2 was dispersed on the carbon nanotubes with a good loading effect and high loading efficiency without agglomeration. The catalyst exhibits a strong ability to absorb light in the ultraviolet region and some ability to absorb light in the visible light region. The CeO2/CNTs nanocomposites photocatalyst was used to degrade azo dye Acid Orange 7 (40 mg/L). The optical decolorization rate was 66.58% after xenon lamp irradiation for 4 h, which is better than that of commercial CeO2 (43.13%). The results suggested that CeO2 loading on CNTs not only enhanced the optical decolorization rate but also accelerated the separation of CeO2/CNTs and water.
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Abstract

In this work, a design equation was presented for a batch-recirculated photoreactor composed of a packed bed reactor (PBR) with immobilised TiO2-P25 nanoparticle thin films on glass beads, and a continuous-flow stirred tank (CFST). The photoreactor was studied in order to remove C.I. Acid Orange 7 (AO7), a monoazo anionic dye from textile industry, by means of UV/TiO2 process. The effect of different operational parameters such as the initial concentration of contaminant, the volume of solution in CFST, the volumetric flow rate of liquid, and the power of light source in the removal efficiency were examined. A rate equation for the removal of AO7 is obtained by mathematical kinetic modelling. The results of reaction kinetic analysis indicate the conformity of removal kinetics with Langmuir-Hinshelwood model (kL-H = 0.74 mg L-1 min-1, Kads = 0.081 mg-1 L). The represented design equation obtained from mathematical kinetic modelling can properly predict the removal rate constant of the contaminant under different operational conditions (R2 = 0.963). Thus the calculated and experimental results are in good agreement with each other.
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