Nitrate adsorption by synthetic activated carbon magnetic nanoparticles: kinetics, isotherms and thermodynamic studies

2015 ◽  
Vol 57 (35) ◽  
pp. 16445-16455 ◽  
Author(s):  
Roshanak Rezaei Kalantary ◽  
Emad Dehghanifard ◽  
Anoushiravan Mohseni-Bandpi ◽  
Leila Rezaei ◽  
Ali Esrafili ◽  
...  
Keyword(s):  
Activated Carbon ◽  
Magnetic Nanoparticles ◽  
Thermodynamic Studies ◽  
Nitrate Adsorption

scholarly journals Adsorption of Nitrate onto ZnCl2-Modified Coconut Granular Activated Carbon: Kinetics, Characteristics, and Adsorption Dynamics

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Lingjie Liu ◽  
Min Ji ◽  
Fen Wang
Keyword(s):  
Activated Carbon ◽  
Granular Activated Carbon ◽  
Kinetic Studies ◽  
Surface Characteristics ◽  
Electrostatic Attraction ◽  
Batch Adsorption ◽  
Dynamic Adsorption ◽  
Batch Experiments ◽  
Nitrate Adsorption ◽  
Pseudo Second Order

Coconut granular activated carbon (CGAC) was modified by impregnating with ZnCl2solution to remove nitrate from aqueous solutions. Sorption isotherm and kinetic studies were carried out in a series of batch experiments. Nitrate adsorption of both ZnCl2-modified CGAC and CGAC fitted the Langmuir and Freundlich models. Batch adsorption isotherms indicated that the maximum adsorption capacities of ZnCl2-modified CGAC and CGAC were calculated as 14.01 mgN·g−1and 0.28 mgN·g−1, respectively. The kinetic data obtained from batch experiments were well described by pseudo-second-order model. The column study was used to analyze the dynamic adsorption process. The highest bed adsorption capacity of 1.76 mgN·g−1was obtained by 50 mgN·L−1inlet nitrate concentration, 20 g adsorbents, and 10 ml·min−1flow rate. The dynamic adsorption data were fitted well to the Thomas and Yoon–Nelson models with coefficients of correlationR2 > 0.834 at different conditions. Surface characteristics and pore structures of CGAC and ZnCl2-modified CGAC were performed by SEM and EDAX and BET and indicated that ZnCl2had adhered to the surface of GAC after modified. Zeta potential, Raman spectra, and FTIR suggested the electrostatic attraction between the nitrate ions and positive charge. The results revealed that the mechanism of adsorption nitrate mainly depended on electrostatic attraction almost without any chemical interactions.

Optimizing Cu(II) removal from aqueous solution by magnetic nanoparticles immobilized on activated carbon using Taguchi method

2016 ◽  
Vol 74 (1) ◽  
pp. 38-47 ◽  
Author(s):  
Mohammad Javad Ebrahimi Zarandi ◽  
Mahmoud Reza Sohrabi ◽  
Morteza Khosravi ◽  
Nafiseh Mansouriieh ◽  
Mehran Davallo ◽  
...  
Keyword(s):  
Aqueous Solution ◽  
Activated Carbon ◽  
Magnetic Nanoparticles ◽  
Signal To Noise Ratio ◽  
Optimization Method ◽  
Uptake Capacity ◽  
Batch System ◽  
Removal Experiments ◽  
Main Effects ◽  
Magnetic Nanoparticles Fe3o4

This study synthesized magnetic nanoparticles (Fe3O4) immobilized on activated carbon (AC) and used them as an effective adsorbent for Cu(II) removal from aqueous solution. The effect of three parameters, including the concentration of Cu(II), dosage of Fe3O4/AC magnetic nanocomposite and pH on the removal of Cu(II) using Fe3O4/AC nanocomposite were studied. In order to examine and describe the optimum condition for each of the mentioned parameters, Taguchi's optimization method was used in a batch system and L9 orthogonal array was used for the experimental design. The removal percentage (R%) of Cu(II) and uptake capacity (q) were transformed into an accurate signal-to-noise ratio (S/N) for a ‘larger-the-better’ response. Taguchi results, which were analyzed based on choosing the best run by examining the S/N, were statistically tested using analysis of variance; the tests showed that all the parameters’ main effects were significant within a 95% confidence level. The best conditions for removal of Cu(II) were determined at pH of 7, nanocomposite dosage of 0.1 gL−1 and initial Cu(II) concentration of 20 mg L−1 at constant temperature of 25 °C. Generally, the results showed that the simple Taguchi's method is suitable to optimize the Cu(II) removal experiments.

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