Micro-Pollutant Research Centre (MPRC), Department of Water and Environmental Engineering, Faculty of Civil Engineering & Built Environment, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia.
Department of Applied Microbiology, Faculty of Applied Sciences, Taiz University, Taiz, Yemen; Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia (UTHM), Pagoh Higher Education Hub, KM 1, Jalan Panchor, 84000 Panchor, Johor, Malaysia.
J Hazard Mater. 2021 Oct 5;419:126500. doi: 10.1016/j.jhazmat.2021.126500. Epub 2021 Jun 26.
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 ppm); CZ-BNC-APP dosage (10, 55 and 100 mg/L); time (10, 55 and 100 min), temperature (20, 32.5 and 45 °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 nm. 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 ppm CFX, 60.60 mg/L of CZ-BNC-APP, after 97.55 min and at 35 °C, the real maximum removal was 95.53% with 100.52 mg g 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.
本研究旨在探讨新型 Cu-Zn 生物纳米复合材料（由南瓜皮培养基中 Aspergillus arenarioides EAN603 的次级代谢产物合成）对头孢氨苄（CFX）的去除效率。该研究基于 CFX 浓度（1、10.5 和 20 ppm）、CZ-BNC-APP 用量（10、55 和 100 mg/L）、时间（10、55 和 100 min）和温度（20、32.5 和 45°C）进行优化。人工神经网络（ANN）模型用于了解 CFX 行为，以研究影响去除过程的因素。CZ-BNC-APP 呈不规则形状，具有多孔结构，尺寸在 20 至 80nm 之间。傅里叶变换红外光谱（FTIR）检测到 CC、C-O 和 OH 基团。ANN 模型表明，CZ-BNC-APP 用量在去除过程中起着至关重要的作用，同时去除过程具有热力学性质。通过 12.41ppm CFX、60.60mg/L 的 CZ-BNC-APP、97.55min 和 35°C 的条件优化 CFX 去除，实际最大去除率为 95.53%，最大吸附容量为 100.52mg/g，拟合系数为 99.5%。CFX 在 CZ-BNC-APP 上的吸附符合伪二级动力学模型和 Langmuir 及 Freundlich 等温吸附模型。这些结果表明，CZ-BNC-APP 具有去除 CFX 的巨大潜力。
