Decolorization of anthraquinone dye Reactive Blue 4 by natural manganese mineral

Zhai, Jun; Wang, Quanfeng; Zou, Jinsong; Wang, Kunping; Xiao, Hai; Huang, Zejin; Rahaman, Md. Hasibur; Habineza, Alphonse

doi:10.5004/dwt.2017.20161

Cited by 1 publication

(2 citation statements)

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“…88±1.3% (Zhaia et al, 2017) 84% (Afreen et al, 2018) 86.8 (Overton, 2018) 80-90% (Neti and Misra, 2012) 83% (Zhang et al, 2015) 73% (Marcelo et al, 2018) 90% (Yemendzhiev et al, 2009) 89% (Maurya et al, 2020)…”

Section: Removal Efficiencies Referencesmentioning

confidence: 99%

“…From the detail literature as discussed above, it is observed that there are very few studies available to remove Reactive Blue 4 (RB 4) from aqueous solutions using electrochemical process, electrocoagulation (EC). The aqueous streams containing RB 4 are treated using some other processes such as biodegradation, adsorption, oxidation, etc., in few studies (Yemendzhiev et al, 2009;Neti and Misra, 2012;Zhaia et al, 2017;Afreen et al, 2018;Marcelo et al, 2018;Overton, 2018;Maurya et al, 2020). Therefore, this study is aimed to treat RB 4 containing wastewater using electro-coagulation (EC), a green electrochemical process as very recently, this process is reviewed critically and found to be better alternative by many researchers (Jing et al, 2021;Lu et al, 2021;Nidheesh et al, 2021;Bhagya Raj and Dash, 2022;Shokri and Fard, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Electrochemical Treatment of Wastewater containing Reactive Blue 4 (RB4) Dye: RSM and ANN Optimization, Technoeconomic Analysis and Sludge Characterization

Gautam,

Kumar,

Sonawane

et al. 2024

Preprint

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In the present study, electrochemistry based electro-coagulation (EC) process, as a green approach is used for the decolorization of Reactive Blue 4 (RB4) from simulated wastewater. A multivariate approach, response surface methodology (RSM) and central composite design (CCD) is employed to model and optimize the EC process with five input variables (pH, initial concentration of dye, current density, operating time, and electrodes gap) to treat the wastewater containing RB4 dye. The efficiency of EC process is calculated in terms of % decolourization and chemical oxygen demand (COD) removal. A back-propagation Artificial Neural Network (BP - ANN) is also engaged to predict the % colour and % COD removal. The experimental values of %decolourization (89.3%) and COD removal (84.3%) are found very close to predicted %decolourizations (88.6% and 89.4%) and COD removal (83.4% and 84.4%) at optimized conditions [pH (X1) = 7.0; initial dye concentration (X2) = 1297.6 mgL-1; current density (X3) = 13.42 mAcm-2; contact time (X4) = 70 min and initial electrodes gap (X5) = 1.0 cm] using RSM and ANN, respectively. Techno-economic efficacy is determined in terms of an operating cost as Rs. 114.82 m-3. The physico-chemical properties of the EC process generated sludge are analyzed using FTIR and FESEM/EDX. The comparative analysis with previous studies and future perspectives of the EC process for the removal of RB4 from wastewater is also carried out.

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