Farhad Khamchin Moghadm - Assistant Professor, Faculty of Engineering, Islamic Azad University of Mashhad, Mashhad, Iran
Mohammad Pakizehrouh - Master of Civil Engineering, Water Engineering and Hydraulic Structures, Islamic Azad University of Mashhad, Iran
Farzane Rezaei Ranjbar - Master of Civil Engineering, Water Engineering and Hydraulic Structures, Islamic Azad University of Mashhad, Iran

Pollution of water resources is one of the human socities’s problems due to the entry of industrial, agricultural, domestic and hospital effluent and wastewater. Hazardous chemical compounds in detergents, pesticides and other industrial materials always endanger the health of humans and the environment, and after reaching the water resources, new purification methods are needed. One of these technologies in the water refinement industry is the use of nanotechnology. For this purpose, after modeling the compounds, some parameters such as composition stability, volume, molecular surface, dipole and toxicity level were calculated by using computer software. An artificial neural network system (ANN) was also used to analyze the above parameters. In this regard, the correlation between different parameters was determined and then the control error and the test error were analyzed and the effective parameter for removing contaminating compounds in different modes, such as the presence and absence of carbon nanotubes and graphene, positioning, nanotubes and graphene length were identifed.

astewater, Chemical Compounds, Nanotechnology, Carbon Nanotubes, Graphene, Artificial Neural Network