Application of linear and non-linear methods for modeling removal efficiency of textile dyes from aqueous solutions using magnetic Fe3O4 impregnated onto walnut shell.
The performance of the Nano-magnetite Fe3O4 impregnated onto walnut shell (Fe3O4-WNS), which possessed the adsorption features of walnut shell and the magnetic property of Fe3O4, was investigated for the elimination of the methyl violet and Rhodamine 6G from contaminated aqueous solutions. The effects of different experimental variables on the removal efficiency of the cited dyes were examined. Then these variables were used as the inputs to generate linear and non-linear models such as the multiple linear regression, random forest, and artificial neural network to predict the removal efficiency of these dye species at different experimental conditions. The validation studies of these models were performed using the test set, which was not present in the modeling procedure. It was found that ANN had a higher ability to predict the adsorption process under different experimental conditions, and could be applied for the development of an automated dye wastewater removal plant. Also the maximum adsorption capacity (qmax) indicated that the qmax value for Fe3O4-WNS for removal of cationic dyes was comparable or better than that for some reported adsorbents. Also it should be cited that exhausted Fe3O4-WNS was regenerated using dishwashing liquid, and reused for removal of the cited dye species from aqueous solutions.
['Ashrafi|Motahare|M|', 'Arab Chamjangali|Mansour|M|', 'Bagherian|Ghadamali|G|', 'Goudarzi|Nasser|N|']
D000327:Adsorption D000465:Algorithms D004396:Coloring Agents D004058:Diffusion D005290:Ferric Compounds D005840:Gentian Violet D006863:Hydrogen-Ion Concentration D031324:Juglans D007700:Kinetics D016014:Linear Models D008280:Magnetics D008958:Models, Molecular D008962:Models, Theoretical D016571:Neural Networks, Computer D017711:Nonlinear Dynamics D009994:Osmolar Concentration D012235:Rhodamines D017550:Spectroscopy, Fourier Transform Infrared D013696:Temperature D013784:Textiles D013997:Time Factors D014874:Water Pollutants, Chemical D018508:Water Purification D014961:X-Ray Diffraction
Non-linear model Multiple linear regression Random forest Artificial neural network Dye removal