Synthesis and Characterization of Titania Photocatalyst Nano-particles of Controlled size and Shapes for waste water treatment

Titania nanotube was synthesized through the hydrothermal route and used for the degradation of azo dye (Sulfan blue) by means of photocatalysis process. The particle sizes, surface morphology, crystal structure were characterized by field emission scanning electron microscopy (FESEM), transmission...

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Bibliographic Details
Main Author: Khethiwe, Judith Mkhatshwa
Format: Final Year Project
Language:English
Published: Universiti Teknologi PETRONAS 2013
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Online Access:http://utpedia.utp.edu.my/8466/1/KHETHIWE%20JUDITH%20MKHATSHWA%20%2814141%29.pdf
http://utpedia.utp.edu.my/8466/
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Summary:Titania nanotube was synthesized through the hydrothermal route and used for the degradation of azo dye (Sulfan blue) by means of photocatalysis process. The particle sizes, surface morphology, crystal structure were characterized by field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), X-ray diffraction (XRD) and Brunauer-Emmett-Teller (BET). The length of the tubes were found to be 150-300nm from the FESEM and BET measured a surface area of 277.17 m2/g, the adsorption model on the titanate nanotube and titania follows the type v Isotherm (multilayer) . The XRD surfaced a formation of anatase phased TiO2. The degradation of Sulfan blue dye was more favourable in alkaline solution, with an optimum (pH 14) while varying the dosage of the TiO2 from (0.025-0.2) g revealed an increase in the rate of degradation, the optimum dosage was found to be 0.2 g. Furthermore, the titania nanotube degradation rate was higher compared to the commercial TiO2 (p25) because of the larger surface area. The adsorption kinetics for the adsorption was done following the type 1 pseudo first order model, type 1 pseudo second order model among others for a comparison between commercial titania and titanate nanotube. The adsorption kinetics display that the degradation follows a type 1 Pseudo second order model.