scholarly journals Statistical optimization of process variables by response surface methodology to enhance phenol degradation by Pseudomonas putida (NCIM 2102)

2011 ◽  
Vol 02 (04) ◽  
pp. 175-181 ◽  
Author(s):  
Velluru Sridevi ◽  
M. V. V Chandana Lakshmi ◽  
A. V. N Swamy ◽  
M Narasimha Rao
Keyword(s):  
Response Surface Methodology ◽  
Pseudomonas Putida ◽  
Response Surface ◽  
Phenol Degradation ◽  
Statistical Optimization ◽  
Process Variables

scholarly journals Optimizing Adsorption of 17α-Ethinylestradiol from Water by Magnetic MXene Using Response Surface Methodology and Adsorption Kinetics, Isotherm, and Thermodynamics Studies

Molecules ◽  
2021 ◽  
Vol 26 (11) ◽  
pp. 3150
Author(s):  
Mengwei Xu ◽  
Chao Huang ◽  
Jing Lu ◽  
Zihan Wu ◽  
Xianxin Zhu ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Quadratic Model ◽  
Adsorption Efficiency ◽  
Process Variables ◽  
Adsorption Time ◽  
Initial Concentration ◽  
Independent Variables ◽  
The Impact ◽  
Adsorbent Dose

Magnetic MXene composite Fe3O4@Ti3C2 was successfully prepared and employed as 17α-ethinylestradiol (EE2) adsorbent from water solution. The response surface methodology was employed to investigate the interactive effects of adsorption parameters (adsorption time, pH of the solution, initial concentration, and the adsorbent dose) and optimize these parameters for obtaining maximum adsorption efficiency of EE2. The significance of independent variables and their interactions were tested by the analysis of variance (ANOVA) and t-test statistics. Optimization of the process variables for maximum adsorption of EE2 by Fe3O4@Ti3C2 was performed using the quadratic model. The model predicted maximum adsorption of 97.08% under the optimum conditions of the independent variables (adsorption time 6.7 h, pH of the solution 6.4, initial EE2 concentration 0.98 mg L−1, and the adsorbent dose 88.9 mg L−1) was very close to the experimental value (95.34%). pH showed the highest level of significance with the percent contribution (63.86%) as compared to other factors. The interactive influences of pH and initial concentration on EE2 adsorption efficiency were significant (p < 0.05). The goodness of fit of the model was checked by the coefficient of determination (R2) between the experimental and predicted values of the response variable. The response surface methodology successfully reflects the impact of various factors and optimized the process variables for EE2 adsorption. The kinetic adsorption data for EE2 fitted well with a pseudo-second-order model, while the equilibrium data followed Langmuir isotherms. Thermodynamic analysis indicated that the adsorption was a spontaneous and endothermic process. Therefore, Fe3O4@Ti3C2 composite present the outstanding capacity to be employed in the remediation of EE2 contaminated wastewaters.

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