title: Application of linear and non-linear methods for modeling removal efficiency of textile dyes from aqueous solutions using magnetic Fe3O4impregnated onto walnut shell.
abstract: The performance of the Nano-magnetite Fe3O4impregnated 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 qmaxvalue 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.
authors.affiliation: College of Chemistry, Shahrood University of Technology, Shahrood, P.O. Box 36155-316, Iran.
authors.forename: Motahare
authors.initials: M
authors.lastname: Ashrafi
authors.affiliation: College of Chemistry, Shahrood University of Technology, Shahrood, P.O. Box 36155-316, Iran.
authors.forename: Mansour
authors.initials: M
authors.lastname: Arab Chamjangali
authors.affiliation: College of Chemistry, Shahrood University of Technology, Shahrood, P.O. Box 36155-316, Iran. Electronic address: Gh_Bagherian@shahroodut.ac.ir.
authors.forename: Ghadamali
authors.initials: G
authors.lastname: Bagherian
authors.affiliation: College of Chemistry, Shahrood University of Technology, Shahrood, P.O. Box 36155-316, Iran.
authors.forename: Nasser
authors.initials: N
authors.lastname: Goudarzi
mesh_terms: D000327:Adsorption; D000465:Algorithms; D004396:Coloring Agents / Q000737:chemistry / Q000302:isolation & purification*; D004058:Diffusion; D005290:Ferric Compounds / Q000737:chemistry*; D005840:Gentian Violet / Q000737:chemistry / Q000302:isolation & purification; D006863:Hydrogen-Ion Concentration; D031324:Juglans / Q000737:chemistry*; 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 / Q000737:chemistry / Q000302:isolation & purification; D017550:Spectroscopy, Fourier Transform Infrared; D013696:Temperature; D013784:Textiles; D013997:Time Factors; D014874:Water Pollutants, Chemical / Q000302:isolation & purification; D018508:Water Purification / Q000379:methods*; D014961:X-Ray Diffraction
chemical_list: D004396:Coloring Agents; D005290:Ferric Compounds; D012235:Rhodamines; D014874:Water Pollutants, Chemical; C026188:rhodamine 6G; C000499:ferric oxide; D005840:Gentian Violet
keywords: Artificial neural network; Dye removal; Multiple linear regression; Non-linear model; Random forest