Response Surface Methodology Applied for Phenol Photocatalytic Degradation in TiO2-P25/Activated Carbon

2014 ◽  
Vol 1 (1) ◽  
pp. 17-22
Author(s):  
Sze-Mun Lam ◽  
Jin-Chung Sin ◽  
Abdul Mohamed
Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 1068
Author(s):  
Emmanuel Kweinor Tetteh ◽  
Elorm Obotey Ezugbe ◽  
Dennis Asante-Sackey ◽  
Edward Kwaku Armah ◽  
Sudesh Rathilal

Water decontamination still remains a major challenge to some developing countries not having centralized wastewater systems. Therefore, this study presents the optimization of photocatalytic degradation of Basic Blue 41 dye in an aqueous medium by an activated carbon (AC)-TiO2 photocatalyst under UV irradiation. The mesoporous AC-TiO2 synthesized by a sonication method was characterized by X-ray diffraction (XRD) and Fourier-transform infrared (FTIR) spectroscopy for crystal phase identification and molecular bond structures, respectively. The efficiency of the AC-TiO2 was evaluated as a function of three input variables viz. catalyst load (2–4 g), reaction time (15–45 min) and pH (6–9) by using Box-Behnken design (BBD) adapted from response surface methodology. Using color and turbidity removal as responses, a 17 run experiment matrix was generated by the BBD to investigate the interaction effects of the three aforementioned input factors. From the results, a reduced quadratic model was generated, which showed good predictability of results agreeable to the experimental data. The analysis of variance (ANOVA), signposted the selected models for color and turbidity, was highly significant (p < 0.05) with coefficients of determination (R2) values of 0.972 and 0.988, respectively. The catalyst load was found as the most significant factor with a high antagonistic impact on the process, whereas the interactive effect of reaction time and pH affected the process positively. At optimal conditions of catalyst load (2.6 g), reaction time (45 min), and pH (6); the desirability of 96% was obtained by a numerical optimization approach representing turbidity removal of 93% and color of 96%.


Author(s):  
Abrar Muslim ◽  
Marwan Marwan ◽  
Ramli Saifullah ◽  
Muhammad Yahya Azwar ◽  
Darmadi Darmadi ◽  
...  

Author(s):  
Mohamed M. Arêmou Daouda ◽  
Akuemaho V. Onésime Akowanou ◽  
S. E. Reine Mahunon ◽  
Chris K. Adjinda ◽  
Martin Pépin Aina ◽  
...  

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