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    Hydrogen purification using natural zeolite-loaded hydroxyethyl cellulose membrane
    (John Wiley and Sons Ltd, 2022) Ünügül, Tuba; Nigiz, Filiz Uğur
    In this study, natural zeolite-loaded hydroxyethyl cellulose (HEC) mixed-matrix membranes were produced and used for separation of hydrogen (H2) from carbon dioxide (CO2). Structural, thermal, and morphological properties of the mixed-matrix membranes were investigated. The effects of zeolite addition and trans-membrane pressure on the gas permeability and H2/CO2 selectivity have been evaluated. As the zeolite ratio in the membrane increased, H2/CO2 selectivity increased. The highest H2/CO2 selectivity of 8.85 was obtained using 20 wt% of natural zeolite-loaded membrane at a constant pressure difference of 4 bar. The selectivity and permeability values of 20 wt% zeolite-loaded membrane exceeded the Robeson's upper bound curve-1991.
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    Optimization of Pervaporative Desalination with Zirconia Based Metal Organic Framework Filled Nanocomposite Membrane
    (Springer, 2023) Ünügül, Tuba; Nigiz, Filiz Uğur; Karakoca, Betül
    In this study, a freestanding asymmetric polylactic acid-based MIL 140A loaded nano-composite membranes were prepared and tested for pervapoative desalination. The chemical and morphological properties of the membranes were characterized by using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The effects of permeate pressure (10, 20, 30 mbar), feed temperature (40, 50, 60 °C), and NaCl concentration (2, 4, 6 wt.%) on the flux and the rejection were experimentally determined. In order to determine the effect of operation parameters on desalination, an optimization study was done using the Box–Behnken design (BBD) of Response Surface Method (RSM) and a statistical model was created. In addition to optimization, experimental studies were also carried out between the limit factors and the results were compared with the model. The highest flux was obtained as 5.40 kg/m2h accompanied with the rejection of 99.87% when at the lowest NaCl content of 2 wt.%, and the highest temperature of 60 °C. The rejection value was greater than 99.7% in all experiments. The highest flux was obtained as 5.40 and 5.44 kg/m2h, respectively, in the experimental and model study at the NaCl content of 2 wt.%, the temperature of 60 °C, and downstream pressure of 10 mbar. It was seen that the most suitable statistical model equation for the experimental results was the second-order quadratic model, and the experimental data were agreed with 99.41% of accuracy.
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    Optimization of Sodium Alginate?Graphene Nanoplate?Kaolin Bio?composite Adsorbents in Heavy Metal Adsorption by Response Surface Methodology (RSM)
    (Springer, 2022) Ünügül, Tuba; Nigiz, Filiz Uğur
    In this study, graphene nanoplate-kaolin-sodium alginate (GKS) bio-composite adsorbent was prepared, and the copper removal from wastewater by the adsorption method was investigated. Characterization of adsorbent was carried out using a scanning electron microscope, Fourier transforms infrared spectroscopy, and thermo-gravimetric analysis methods. In addition to the parametric adsorption studies, experimental optimization was also applied with parameters determined by the central composite design of response surface methodology (RSM). Effects of copper concentration (from 10 to 50 ppm), pH (from 3 to 7), and adsorption dosage (from 0.05 to 0.15 g/L) were investigated to determine the optimum design points. In order to determine the efficiency of heavy metal adsorption, four experimental parameters (adsorbent dosage, metal concentration, pH, and contact time) were evaluated. As a result, the highest removal of 92.12% was obtained when the heavy metal concentration was 10 mg/L, the adsorbent dosage was 0.15 g, the solution pH was 7, and the contact time was 180 min. Adsorption isotherm studies were also carried out. The appropriate adsorption isotherm for copper removal using GKS was determined as Langmuir isotherm. According to the optimization results, the quadratic model with an R2 of 0.9946 was found to be the most suitable model.