Bifunctional composite from spent “Cyprus coffee” for tetracycline removal and phenol degradation: Solar-Fenton process and artificial neural network - Oladipo, Akeem Adeyemi; Ali Abureesh, Mosab; Gazi, Mustafa (Elsevier, 2015)
Removals of tetracycline and photocatalytic degradation of phenol by Fe3O4/coffee residue (MCC) were investigated. Brunauer–Emmett–Teller (BET), vibrating sample magnetometer (VSM) and Boehm titration were employed to characterize MCC. Artificial neural network (ANN) model was developed to predict the tetracycline (TC) concentration in the column effluent. Maximum tetracycline adsorption capacity of 285.6 mg/g was observed in a batch system. High removal efficiency (87%) was obtained at 3.3 mL/min flow rate, 8.0 cm bed height and 50 mg/L influent TC concentration in a column system. Complete degradation of phenol by solar-Fenton was attained at 60 min irradiation time. Total organic carbon (TOC) removal increased to 63.3% in the presence of 1.0 g/L MCC, 1.2 g/L H2O2 and solar irradiation. MCC showed remarkable potential to remove antibiotics from wastewater even in the presence of heavy metal (Ni2+) via magnetic separation.
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Keywords: Coffee residue; Antibiotics; Magnetic separation; Fixed-bed Phenol; Artificial neural network