Yazar "Khataee, Alireza" seçeneğine göre listele

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    Enhancing the permeability and antifouling properties of cellulose acetate ultrafiltration membrane by incorporation of ZnO@graphitic carbon nitride nanocomposite
    (Elsevier Sci Ltd, 2021) Vatanpour, Vahid; Faghani, Somayeh; Keyikoğlu, Ramazan; Khataee, Alireza
    This study reports the modification of cellulose acetate (CA) membrane with zinc oxide (ZnO)@graphitic carbon nitride (g-C3N4) nanocomposite to improve the antifouling and separation performance. Different combinations of the CA-based membranes such as CA/g-C3N4, CA/ZnO, and CA/ZnO@g-C3N4 were fabricated using the non solvent induced phase separation (NIPS) method. Membranes were analyzed for their morphology (SEM), porosity, pore size, contact angle, permeability, rejection, and antifouling properties. According to the SEM images of CA/ZnO@g-C3N4, the formation of pear-shaped macro voids and finger-like canals originating from the top layer was evident. Nanocomposite blended membrane with 0.25 wt.% ZnO@g-C3N4 achieved the largest pore radius (3.05 nm) and the lowest contact angle (67.7 degrees). With these characteristics, 0.25 wt.% ZnO@g-C3N4 membrane obtained a pure water flux of 51.3 LMH, which is 2.1 times greater than the bare CA and high BSA and dye rejections with 97.20% and 93.7% respectively. Finally, the antifouling resistance of the CA membrane was greatly improved with FRR increasing from 73.7% to 94.8%, which was accompanied by a significant decrease in the fouling resistance parameters.
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    High-performance carbon black electrode for oxygen reduction reaction and oxidation of atrazine by electro-Fenton process
    (Elsevier, 2021) Karataş, Okan; Gengec, Nevin Atalay; Gengec, Erhan; Khataee, Alireza; Kobya, Mehmet
    The aim of this study is to produce an electrode that can be used in H2O2 production and Electro-Fenton (EF) process by an effective, cheap, and easy method. For this reason, a superhydrophobic electrode with a higher PTFE ratio and high thickness was produced with a simple press. The produced electrode was used in the production of H2O2 and mineralization of Atrazine. First, the effect of pH, cathode voltage, and operation time on H2O2 production was evaluated. The maximum H2O2 concentration (409 mg/L), the highest current efficiency (99.80%), and the lowest electrical energy consumption (3.16 kWh/kg) were obtained at 0.8 V, 7.0 of pH, and 120 min, and the stability of the electrode was evaluated up to 720 min. Then, the effects of the operational conditions (pH, cathode voltage, operating time, and catalyst concentration) in electro-Fenton were evaluated. The fastest degradation of Atrazine (>99%) was obtained at 2.0 V, 3.0 of pH, and 0.3 mM of Fe2+ in 15 min. In the final part of the study, the degradation intermediates were identified, and the characterization of the electrode was evaluated by SEM, XRD, FT-IR, tensiometer, potentiostat, and elemental analyzer.
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    Machine Learning for Advanced Design of Nanocomposite Ultrafiltration Membranes
    (American Chemical Society, 2021) Fetanat, Masoud; Keshtiara, Mohammadali; Low, Ze-Xian; Keyikoğlu, Ramazan; Khataee, Alireza
    Although the incorporation of nanoparticles into ultrafiltration polymeric membranes has shown promising outcomes, their commercial implementation has yet to be fulfilled due to inconsistency in data, lack of a reliable recipe for the optimum filler content, and reluctance in disrupting the production line which requires significant time and resources. There is a growing demand among membrane communities for a design platform that can accelerate the discovery of new nanocomposite membranes. In this work, a feed-forward ANN (artificial neural network) model that has one hidden layer and the Bayesian regularization training algorithm were chosen for designing a graphical user interface platform to predict the ultrafiltration nanocomposite membrane performance, that is, solute rejection, flux recovery, and pure water flux, thereby saving time and resources used in membrane design. Experimental data (735 samples from 200 reports published between 2006 and 2020) were derived from the literature for training, validation, and testing of the ANN models. The results indicated that the best 30 ANN models produce the most accurate estimation of membrane performance using the seven input variables of polymer concentration, polymer type, filler concentration, average filler size, solvent concentration (in the dope solution), solvent type, and contact angle on the unseen data set. Furthermore, a sensitivity analysis was performed on the achieved models to identify the most effective input variables for each nanocomposite membrane performance. This work has the potential to be extended to other mixed matrix membrane types that are going to be used for microfiltration, nanofiltration, reverse osmosis, and so forth.
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    Machine learning for design of thin-film nanocomposite membranes
    (Elsevier B.V., 2021) Fetanat, Masoud; Keshtiara, Mohammadali; Keyikoğlu, Ramazan; Khataee, Alireza; Daiyan, Rahman; Razmjou, Amir
    In this study, a novel machine learning approach is proposed for estimation of the permeate flux and foulant rejection in nanocomposite filtration membranes. Nine independent variables are fed to artificial neural networks (ANNs) including support, nanoparticles concentration, concentration of organic phase trimesoyl chloride (TMC) in-n-hexane (TMC in n-hexane), operation pressure, contact angle, thin layer thickness, location of the nanoparticles (NPs), post-treatment temperature and duration, and permeate flux and foulant rejection were derived as the outputs of the ANNs. The proposed method was evaluated on two datasets across training, validation and test datasets, and an unseen dataset. 2250 different initial weights and number of the neurons in the hidden layer for the proposed ANN models were considered and compared to find the optimized ANN models. The mean squared error (MSE) and coefficient of determination (R2) were employed to select the best 20 ANN models for further analysis. The proposed ANN models resulted in accurate estimates for both permeate flux and foulant rejection with R2 of 0.9958 and 0.9412 in all data included in the training, validation and test datasets and R2 of 0.9938 and 0.9811 in unseen dataset, respectively. In addition, results of sensitivity analysis revealed that post treatment temperature and contact angle were found the most important input variables for estimation of permeate flux and foulant rejection. The proposed method can provide valuable insights for formulating permeate flux and foulant rejection and considering the effects of each experimental condition on nanocomposite filtration membranes without doing real experiments, which is time-consuming and expensive.
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    Peroxydisulfate activation by in-situ synthesized Fe3O4 nanoparticles for degradation of atrazine: Performance and mechanism
    (Elsevier, 2020) Keyikoğlu, Ramazan; Karataş, Okan; Khataee, Alireza; Kobya, Mehmet; Can, Orhan Taner; Soltani, Reza Darvishi Cheshmeh
    Herein activation of persoxydisulfate (PDS) was achieved by in-situ synthesized Fe3O4 nanoparticles (NPs) from a sacrificial iron anode in an electrochemical (EC) cell. The as-synthesized Fe3O4 NPs were characterized to be in spherical and in the nano size. The performance of the process, EC-Fe3O4/PDS, was investigated in terms of atrazine (ATZ) degradation. Optimum process conditions were determined as initial pH of 5, electrolyte (Na2SO4) concentration of 1 mM, a current density of 1.67 A m(-2), PDS concentration of 0.5 mM and initial ATZ concentration of 10 mg L-1. At optimum conditions, the EC-Fe3O4/PDS process could effectively degrade 80% of ATZ in an aqueous solution within a short reaction time of 20 min. The electrical energy consumption of the process was found to be quite low with 0.0307 kWh/m(3). Based on the LC/MS analysis, the degradation pathway of ATZ with seven transformation products was proposed. Finally, a possible mechanism of the EC-Fe3O4/PDS process was put forward, which includes the activation of PDS and the role of radicals in the degradation of ATZ. In conclusion, the combination of Fe3O4 NPs catalyzed PDS oxidation with the EC process was very effective in the degradation of ATZ to dechlorinated final products. The strong synergistic effect makes this process superior to conventional methods due to the high degradation efficiency with low electrical energy and chemical consumption. Application of this method, with very low current density, may not only minimize the electrical energy consumption but also help reduce the sludge production due to the lower iron dissolution.
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    A review on treatment of membrane concentrates generated from landfill leachate treatment processes
    (Elsevier, 2021) Keyikoğlu, Ramazan; Karatas, Okan; Rezania, Hamidreza; Kobya, Mehmet; Vatanpour, Vahid; Khataee, Alireza
    Landfill leachate (LL) is highly toxic wastewater and comprises various pollutants such as organic compounds, biological organisms, xenobiotics, heavy metals, inorganic salts, and ammonia. The integration of conventional methods with membrane processes has become indispensable due to the enforcement of stricter regulations for the LL discharge. The integrated membrane technologies achieve a pollutant removal efficiency of higher than 95% with a large volume of treated leachate and a low capital cost investment. However, the drawback of these processes is the production of a membrane concentrate with even more hazardous characteristics. This review presents the state of the art methods along with the recent improvements to the existing processes for the treatment of membrane concentrates. The techniques are mainly divided into two categories of conventional, advanced methods and the hybridization of them. The operating conditions, performances of the individual processes along with wastewater characteristics were summarized in detail. Generally, the leachate concentrate properties such as salinity, COD, BOD5/COD ratio, and toxicity are essential parameters for the selection of appropriate treatment methods. It was found that single treatment processes are not able to reach desirable membrane concentrate treatment and need an engineered combination of these techniques to achieve satisfactory removal efficiencies.