Optimization of batch process parameters using response surface methodology for dye removal by a novel adsorbent

Ravikumar, K.; Pakshirajan, Kannan; Swaminathan, T.; Balu, K.

doi:10.1016/j.cej.2004.10.008

Cited by 176 publications

(94 citation statements)

References 22 publications

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“…Moreover, the contours of the plots help to identify the type of interactions between these variables. The maximum predicted yield was obtained and it was indicated by the surface confined in the smallest curve of the contour diagram [18]. The respective plots are showing the variation in target responses owing to variation in levels of operational parameters.…”

Section: Surface and Contour Plotsmentioning

confidence: 99%

Optimization of Electrocoagulation Process for the Removal of Binary Dye Mixtures Using Response Surface Methodology and Estimation of Operating Cost

Shah¹,

Tahir²,

Ullah³

et al. 2017

OJAppS

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The study was useful for the treatment of Reactive red 223 (R223) and Coomassie brilliant blue R250 (CBBR250) binary dye system by electrocoagulation process (EC). Moreover, the Al and Fe electrode were used as an anode and cathode, respectively. The response surface methodology (RSM) was adopted by utilizing central composite design to plan the experimental runs. The EC process was preceded under the effect of operating parameters including pH, NaCl, voltage and electrolysis time. The % color and COD removals were examined as response variables. The removal efficiency of RR223 and CBBR250 dye at optimum values was 89% and 94% and COD removal was 100%. The kinetic study was performed to determine the rate and rate constant. First and second order kinetic models were studied to figure out the exact mechanism of the dye removal using EC process. The estimated cost of the experimental design about 4.486 US$/dm 3 was also determined. This study showed that EC process is an economical way for the treatment of waste water.

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Section: Surface and Contour Plotsmentioning

confidence: 99%

Optimization of Electrocoagulation Process for the Removal of Binary Dye Mixtures Using Response Surface Methodology and Estimation of Operating Cost

Shah¹,

Tahir²,

Ullah³

et al. 2017

OJAppS

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“…Since, the correlation between the response and input variables are described as a surface of the X 1 , X 2 , coordinates in the graphical sense, hence named the response surface study. [10][11][12] In this design, 3 independent factors were evaluated, each at 3 levels, and experimental trials were performed for all 13 possible combinations. Current density (X 1 ) medium (X 2 ) and HPMC concentration (X 3 ) were chosen as independent variables strength, permeation of drug at 4 h (Q4) Y 1 , amount of drug permeated at 24 h (Q24) Y 2 and lag time h Y 3 were dependent variables.…”

Section: Optimization Of Variables Using Experimental Designmentioning

confidence: 99%

“…[10][11][12] It is an empirical technique developed for analyzing and studying the relationship between set of controlled experimental factors and observed results. 13 To analyze a process mutually with a response Y which mainly depends on the input factors X 1 , X 2 , …, X n , the correlation between the response and the input process parameters are described as Y = f (X 1 , X 2 , …, X n ) + ε, where f is the response function and ε is the error.…”

Section: Optimization Of Variables Using Experimental Designmentioning

confidence: 99%

Use of Box-Behnken Experimental design for Optimization of process Variables in Iontophoretic delivery of Repaglinide

Sriram¹,

Rao²,

Kumar³

2016

JYP

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Objective: In this study, a Box-Behnken design (BBD) of response surface method was used to investigate and optimize the process parameters of Repaglinide. Repaglinide is a suitable candidate for iontophoretic delivery due to its first pass metabolism and frequent dosing, hence transdermal delivery was required to improve bioavailability and patient compliance. The goal was to identify the optimum levels of independent variables intended for the dependent variable. Materials and Method: Independent variables selected were current intensity (X 1 ), medium/pH (X 2 ), polymer (HPMC) concentration (X 3 . The results of statistics between factorial and theoretical profiles were used to select optimized critical process parameters. Conclusion: Thus, it was concluded that optimal use of amount of polymer and current intensity in the permeation of drug could increase the bioavailability and the interactions can be defined as a regression model which is statistically significant.

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“…Nowadays, different methods are available for the treatment of dye wastewaters such as an reverse osmosis, ion exchange, chemical precipitation, ozonation and solvent extraction. However, high capital cost and operational costs or secondary sludge disposal problem are the disadvantages of the mentioned techniques (Daneshvara et al, 2015;Etorki and Massoudi, 2011;Ravikumara et al, 2005). The adsorption technique has significant adantages and it can be accepted as the best way to treat effluents.…”

mentioning

confidence: 99%

“…RSM is the combination of mathematical and statistical techniques for optimizing processes and can be used to investigate both the relative and complex interactions of several factors even (Ravikumara et al, 2005). The application of experimental design in adsorption process can improve product yields, reduce development time and overall costs and reduce process variability (Arunachalam and Annadurai, 2011;Liu et al, 2010).…”

mentioning

confidence: 99%

Removal of Reactive Blue 19 From Aqueous Solution by Peanut Shell: Optimization by Response Surface Methodology

Demırhan¹

2017

Scitech

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ABSTRACT:In the present study, it was aimed to optimize the removal of reactive blue 19 dye by using peanut shells as a low -cost adsorbent. The influence of various process parameters namely pH (2,3 and 4), temperature (25, 35 and 45°C) and adsorbent amount (0.5, 1 and 1.5 g/100 mL) were studied using Box-Behnken design. According to the ANOVA results, the quadratic model with coefficient of determination (R 2 ) value of 0.9984 and model F value of 487.80 was showed good fit of the experimental data to. Experimental conditions for optimum dye removal of 93.45% were determined as pH 2, 35°C and 1.5 g/100 mL adsorbent amount. Langmuir fitted better to the obtained equilibrium data for removal of reactive blue 19 than Freundlich and Temkin models. In addition, the adsorp tion kinetics was also studied for the reactive blue 19 removal onto peanut shell. The kinetic studies showed that the removal of reactive blue 19 fitted to pseudo-second-order model.

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Optimization of batch process parameters using response surface methodology for dye removal by a novel adsorbent

Cited by 176 publications

References 22 publications

Optimization of Electrocoagulation Process for the Removal of Binary Dye Mixtures Using Response Surface Methodology and Estimation of Operating Cost

Optimization of Electrocoagulation Process for the Removal of Binary Dye Mixtures Using Response Surface Methodology and Estimation of Operating Cost

Use of Box-Behnken Experimental design for Optimization of process Variables in Iontophoretic delivery of Repaglinide

Removal of Reactive Blue 19 From Aqueous Solution by Peanut Shell: Optimization by Response Surface Methodology

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