پديدآورندگان :
Razzaghi Mohammad Department of Chemical Engineering, Faculty of Chemical and Petroleum Engineering, University of Tabriz, Tabriz, Iran , Karimi Afzal Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran, , Aghdasinia Hassan Department of Chemical Engineering, Faculty of Chemical and Petroleum Engineering, University of Tabriz, Tabriz, Iran, , Joghatae Mohammad-Taghi Department of Health Services and Health Education, School of Public Health, Iran University of Medical Sciences, Tehran, Iran,
كليدواژه :
Artificial neural network , Genetic algorithm , Glucose Oxidase , Horseradish peroxidase , Phenol.
چكيده فارسي :
In this research, horseradish peroxidase (HRP) and glucose oxidase (GOx) were co-immobilized on the polyurethane, and the resulted HRP/GOx/polyurethane biocatalyst was characterized using scanning electron microscopy (SEM) technique. In order to prevent the deactivation of HRP in the presence of excess H2O2, required H2O2 for activation of HRP was produced in situ by GOx. The resulted HRP/GOx/polyurethane biocatalyst was filled in a packed bed reactor and applied for phenol removal from aqueous solution. The effect of the operational parameters including flow rate and temperature on the removal efficiency of the phenol was investigated. Finally, an artificial neural network (ANN) was developed for modelling and expressing the relationship between the phenol removal efficiency and operational parameters. The optimized values of parameters were determined by optimizing the resulted ANN model using genetic algorithm (GA).
