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Application of response surface methodology and artificial neural network: modeling and optimization of Cr(VI)
Soumaya Harbi1, Fatma Guesmi1, Dorra Tabassi1
1UR11ES17 Desalination and Water Treatment, University of Tunis El Manar, Faculty of Sciences of Tunis, 2092 Tunis, Tunisia
Abstract:
We report the adsorption efficiency of Cr(VI) on a strong anionic resin Dowex 1X8. The Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) analysis of this adsorbent were investigated. Response surface methodology was applied to evaluate the main effects and interactions among initial pH, initial Cr(VI) concentration, adsorbent dose and temperature. Analysis of variance depicted that resin dose and initial pH were the most significant factors. Desirability function (DF) showed that the maximum Cr(VI) removal of 95.96% was obtained at initial pH 5, initial Cr(VI) concentration of 100 mg/L, resin dose of 2 g and temperature of 283 K. Additionally, a simulated industrial wastewater containing 14.95 mg/L of Cr(VI) was treated successfully by Dowex 1X8 at optimum conditions. Same experimental design was employed to develop the artificial neural network. Both models gave a high correlation coefficient (RRSM(2) = 0.932, RANN(2) = 0.996).
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