Cephalexin removal by a novel Cu-Zn bionanocomposite biosynthesized in secondary metabolic products of Aspergillus arenarioides EAN603 with pumpkin peels medium: Optimization, kinetic and artificial neural network models.

Abstract

The present study aimed to investigate the removal efficiency of cephalexin (CFX) by a novel Cu-Zn bionanocomposite biosynthesized in the secondary metabolic products of Aspergillus arenarioides EAN603 with pumpkin peels medium (CZ-BNC-APP). The optimization study was performed based on CFX concentrations (1, 10.5 and 20\xa0ppm); CZ-BNC-APP dosage (10, 55 and 100\xa0mg/L); time (10, 55 and 100\xa0min), temperature (20, 32.5 and 45\xa0°C). The artificial neural network (ANN) model was used to understand the CFX behavior for the factors affecting removal process. The CZ-BNC-APP showed an irregular shape with porous structure and size between 20 and 80\xa0nm. The FTIR detected CC, C-O and OH groups. ANN model revealed that CZ-BNC-APP dosage exhibited the vital role in the removal process, while the removal process having a thermodynamic nature. The CFX removal was optimized with 12.41\xa0ppm CFX, 60.60\xa0mg/L of CZ-BNC-APP, after 97.55\xa0min and at 35\xa0°C, the real maximum removal was 95.53% with 100.52\xa0mg\xa0g-1 of the maximum adsorption capacity and 99.5% of the coefficient. The adsorption of CFX on CZ-BNC-APP was fitted with pseudo-second-order model and both Langmuir and Freundlich isotherms models. These findings revealed that CZ-BNC-APP exhibited high potential to remove CFX.