Enhanced Removal of Diesel Oil Using New Magnetic Bentonite-Based Adsorbents Combined with Different Carbon Sources

摘要

In this work, new magnetic bentonite-based adsorbents combined with different carbon sources, namely, reduced graphene oxide and mul-tiwall carbon nanotubes, were synthesized via co-precipitation method. The synthesized adsorbents were characterized using XRD, TGA, SEM, EDX, TEM, and BET analysis techniques. The adsorbents were then used to remove oil from aqueous solutions of water-in-oil emulsion by performing batch adsorption experiments. The experimental data were fitted to three isotherm models including Langmuir, Freundlich, and Sips models using non-linear regression and were compared using Akaike Information Criterion statistical model. The data analysis showed that Sips model best fits the experimental data for the adsorption of oil onto both adsorbents. The maximum adsorption capacity of oil from sips model were 81.65 mg/g and 77.12 mg/g for Fe_3O_4/Bent/rGO and Fe_3O_4//Bent/MWCNTs, respectively. The obtained kinetics data were fitted to pseudo-first-order, pseudo-second-order, and intraparticle diffusion models. Pseudo-second order kinetic model best fitted the kinetic data of both adsorbents. Overall, both adsorbents showed high removal efficiency reaching equilibrium in less than 50 min indicating that both adsorbents can be successfully utilized in industrial adsorption process.