Nowadays,widespread researches have been focused on the development of effective photocatalysts to remove pollutants of the aquatic system.In accordance with the universal studies,two new sets of UiO-66@metal oxide(in...Nowadays,widespread researches have been focused on the development of effective photocatalysts to remove pollutants of the aquatic system.In accordance with the universal studies,two new sets of UiO-66@metal oxide(including ZnO and TiO2)/graphene oxide heterojunctions were synthesized for photodegradation of aromatic(tetracycline)and nonaromatic(malathion)pollutants which are challenging cases in the environment.The dosage of the photocatalyst,pH of the solution,the type of metal oxide,and the presence of various scavengers are assayed parameters in this work.In the optimum condition,maximum photodegradation efficiency is achieved in 90 min for tetracycline(81%)and malathion(100%)by the UiO-66@ZnO/graphene oxide.The superior separation of charge carriers by Z-scheme mechanism,excellent electron mobility on layers of graphene oxide and high surface area are factors that enhanced the efficiency.Furthermore,in comparison with pure UiO-66,the band gaps belong to heterojunctions revealed a red shift in the absorption edge,which can be responsible for more expand adsorption of the solar spectrum.Total organic carbon analysis verified the decontamination of these pollutants in the solution.The produced main intermediates during the photocatalytic process were identified and the possible degradation pathway proposed.In general,the superior photocatalytic activity suggests that these designed photocatalysts can be a promising choice for having a clean future.展开更多
This work highlights the application of Artificial Neural Networks optimized by Cuckoo optimization algorithm for predictions of NMR log parameters including porosity and permeability by using field log data.The NMR l...This work highlights the application of Artificial Neural Networks optimized by Cuckoo optimization algorithm for predictions of NMR log parameters including porosity and permeability by using field log data.The NMR logging data have some highly vital privileges over conventional ones.The measured porosity is independent from bearer pore fluid and is effective porosity not total.Moreover,the permeability achieved by exact measurement and calculation considering clay content and pore fluid type.Therefore availability of the NMR data brings a great leverage in understanding the reservoir properties and also perfectly modelling the reservoir.Therefore,achieving NMR logging data by a model fed by a far inferior and less costly conventional logging data is a great privilege.The input parameters of model were neutron porosity(NPHI),sonic transit time(DT),bulk density(RHOB)and electrical resistivity(RT).The outputs of model were also permeability and porosity values.The structure developed model was build and trained by using train data.Graphical and statistical validation of results showed that the developed model is effective in prediction of field NMR log data.Outcomes show great possibility of using conventional logging data be used in order to reach the precious NMR logging data without any unnecessary costly tests for a reservoir.Moreover,the considerable accuracy of newly ANN-Cuckoo method also demonstrated.This study can be an illuminator in areas of reservoir engineering and modelling studies were presence of accurate data must be essential.展开更多
基金financial support of this study by Iran National Science Foundation(INSF)(No.96010030)
文摘Nowadays,widespread researches have been focused on the development of effective photocatalysts to remove pollutants of the aquatic system.In accordance with the universal studies,two new sets of UiO-66@metal oxide(including ZnO and TiO2)/graphene oxide heterojunctions were synthesized for photodegradation of aromatic(tetracycline)and nonaromatic(malathion)pollutants which are challenging cases in the environment.The dosage of the photocatalyst,pH of the solution,the type of metal oxide,and the presence of various scavengers are assayed parameters in this work.In the optimum condition,maximum photodegradation efficiency is achieved in 90 min for tetracycline(81%)and malathion(100%)by the UiO-66@ZnO/graphene oxide.The superior separation of charge carriers by Z-scheme mechanism,excellent electron mobility on layers of graphene oxide and high surface area are factors that enhanced the efficiency.Furthermore,in comparison with pure UiO-66,the band gaps belong to heterojunctions revealed a red shift in the absorption edge,which can be responsible for more expand adsorption of the solar spectrum.Total organic carbon analysis verified the decontamination of these pollutants in the solution.The produced main intermediates during the photocatalytic process were identified and the possible degradation pathway proposed.In general,the superior photocatalytic activity suggests that these designed photocatalysts can be a promising choice for having a clean future.
文摘This work highlights the application of Artificial Neural Networks optimized by Cuckoo optimization algorithm for predictions of NMR log parameters including porosity and permeability by using field log data.The NMR logging data have some highly vital privileges over conventional ones.The measured porosity is independent from bearer pore fluid and is effective porosity not total.Moreover,the permeability achieved by exact measurement and calculation considering clay content and pore fluid type.Therefore availability of the NMR data brings a great leverage in understanding the reservoir properties and also perfectly modelling the reservoir.Therefore,achieving NMR logging data by a model fed by a far inferior and less costly conventional logging data is a great privilege.The input parameters of model were neutron porosity(NPHI),sonic transit time(DT),bulk density(RHOB)and electrical resistivity(RT).The outputs of model were also permeability and porosity values.The structure developed model was build and trained by using train data.Graphical and statistical validation of results showed that the developed model is effective in prediction of field NMR log data.Outcomes show great possibility of using conventional logging data be used in order to reach the precious NMR logging data without any unnecessary costly tests for a reservoir.Moreover,the considerable accuracy of newly ANN-Cuckoo method also demonstrated.This study can be an illuminator in areas of reservoir engineering and modelling studies were presence of accurate data must be essential.
