Islamic Azad University

About: Islamic Azad University is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Population & Catalysis. The organization has 83635 authors who have published 113437 publications receiving 1275049 citations. The organization is also known as: Azad University.

Effective removal of Amoxicillin, Cephalexin, Tetracycline and Penicillin G from aqueous solutions using activated carbon nanoparticles prepared from vine wood

Abstract: The present study shows the applicability of carbon nanoparticles made from vine wood as an inexpensive adsorbent for the removal of Amoxicillin, Cephalexin, Tetracycline and Penicillin G from aqueous solutions. The activation of carbon nanoparticles was studied by aqueous solutions of NaOH, KOH, ZnCl 2 , NaCl and HNO 3 . The removal efficiency ( R %) of pollutants showed that NaOH can be used as an efficient, low-cost and environmentally friendly activator ( R % = 74–88). Infrared spectroscopy, XRD pattern, BET and BJH methods and scanning electron microscope (SEM) images were used to characterize the prepared carbon. The area and pore volume of activated carbon were obtained as 13.397 m 2 /g and 54.79 cm 3 /g, respectively. The SEM images showed a high porosity for activated carbon. Removal of antibiotics from aqueous samples was carried out using a modular method. The optimized parameters of pH 2, an amount of adsorbent of 0.4 g/L, a concentration of antibiotic solution of 20 mg L −1 , a contact time of 8 h and a temperature of 45 °C were obtained in a modular way. Kinetic studies confirmed that the adsorption followed second-order reaction kinetics. Thermodynamic studies revealed that the process was spontaneous and endothermic. The reusability of sorbent was achieved by using of NaOH (5 w/w%) solution and recovery time of 4 h.

Artificial neural network for modeling nitrate pollution of groundwater in marginal area of Zayandeh-rood River, Isfahan, Iran

Abstract: Excessive use of chemical fertilizers, especially nitrogen fertilizers to increase crop and improper purification, and delivery of municipal and industrial wastewater are proposed as factors that increase the amount of nitrate in groundwater in this area. Thus, investigation of nitrate contamination as one of the most important environmental problems in groundwater is necessary. In the present study, modeling and estimation of nitrate pollution in groundwater of marginal area of Zayandeh-rood River, Isfahan, Iran, was investigated using water quality and artificial neural networks. 100 wells (77 agriculture well, 13 drinking well and 10 gardens well) in the marginal area of Zayandeh-rood River, Isfahan, Iran were selected. MATLAB software and three-layer Perceptron network were used. The back-propagation learning rule and sigmoid activation function were applied for the training process. After frequent experiments, a network with one hidden layer and 19 neurons make the least error in the process of network training, testing and validation. ANN models can be applied for the investigation of water quality parameters.