Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2025Scopus SJRQ1/r/bayburt/11191
  Artificial neural network modelling of reactive red 45 Azo dye removal by peroxi-electrocoagulation

  Bayar, S.; Erdoğan, M.; Taşdemir, A.; Kaleli, A.; Paloluoglu, C.

  In the present study, the Peroxi-electrocoagulation process was employed to remove chemical oxygen demand and the decolorization of reactive red 45 dye wastewater. This process offers several advantages, including the oxidation of dye molecules by hydroxyl radicals and coagulation through iron hydroxide precipitation. The reactor was equipped with six iron electrodes, providing a total surface area of 546 cm2. The effects of applied current (0.3–0.18 A), hydrogen peroxide concentration (100–700 mg/L), initial pH (2.5–5.0), and dye concentration (100–500 mg/L) on chemical oxygen demand and color removal were investigated. Optimum operational conditions were determined to be applied current of 0.150 (corresponding to current density of 0.27 mA/cm2), pH of 3.0, H2O2 concentration of 600 mg/L, and dye concentration of 200 mg/L. Under these conditions, COD and color efficiencies reached 83% and > 99%, respectively. The specific energy consumption under optimal conditions was 33.4 kWh/kg COD with 82.8% COD removal. The findings indicate that increasing the applied current and H2O2 concentration enhances removal performance up to a certain threshold, beyond which no significant improvement is observed. This suggests that the availability of electrogenerated reagents governs the overall reaction efficiency. Additionally, an artificial neural network model was developed to predict COD and color removal efficiencies. The network employed a 4:10:2 architecture and was trained using a backpropagation algorithm. Input variables included applied current, pH, H2O2 concentration, and dye concentration. The model exhibited high predictive accuracy, with R2 of 0.9782 for COD removal and 0.9579 for Color removal, confirming the effectiveness of the ANN in modeling.

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  AtıfScopus3·WoS3·OpenAlex4

  İncele
• MakaleAçık Erişim2021Scopus SJRQ1/r/bayburt/12154
  Removal of Cu(II) from aqueous solutions using modified sewage sludge ash

  Kul, S.

  The study aims to determine Cu(II) adsorption from wastewater in the laboratory condition using modified sewage sludge ash as adsorbent which was obtained from a thermal drying and incineration facility. This procedure was completed with an inexpensive pollutant material which has high metal-binding capacity and is available in abundant amounts. During experiments, the effects of particle size, pH, stirring speed, initial ion concentration, adsorbent dosage and temperature were investigated. Adsorption equilibrium was obtained in 10 min. Maximum Cu(II) removal was calculated as 83.63% with 20 mg L−1 initial Cu(II) ion concentration and 5 g L−1 adsorbent dosage. Kolmogorov–Smirnov normality test was performed to test the conformity of the data obtained as a result of the study to variance analysis, and it was determined that the data were distributed normally (p > 0.05). Levene test was performed for homogeneity test, and it was determined that the data were distributed homogeneously (p > 0.05). Langmuir was determined as the most suitable isotherm model for Cu(II) adsorption. Adsorption kinetics abided by the pseudo-second-order model. Based on kinetic studies, the adsorption process was endothermic with maximum adsorption capacity calculated as 7.53 mg g−1. The results of thermodynamic research showed the adsorption reaction was spontaneous (ΔG° < 0), endothermic (ΔH° > 0) and reversible (ΔS° > 0 and close to zero).

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  AtıfScopus10·WoS10·OpenAlex12

  İncele
• MakaleAçık Erişim2021Scopus SJRQ1/r/bayburt/12017
  Pb (II) biosorption from the aqueous solutions by raw and modified tea factory waste (TFW)

  Nuhoğlu, Y.; Ekmekyapar Kul, Z.; Kul, S.; Nuhoğlu, Ç.; Ekmekyapar Torun, F.

  The study is aimed to determine Pb (II) biosorption from synthetic wastewaters using natural and modified tea factory waste as biosorbent material. This process is carried out with this waste matter, which is found in large quantities, so cheap and has high metal adsorption ability. The sorption kinetic studies were determined as variations of initial pH value, particle size, initial Pb (II) and tea factory waste concentrations, stirring speed and temperature. Biosorption reached the equilibrium in 15 min. Zeta potential values of the biosorbent were defined in the range of pH 2 to 4. The adsorption isotherm models give the experimental values, and the thermodynamic characteristics of the patterns generally give insight about the sorption mechanism depending on the surface characteristics and affinity of the biosorbent. The biosorption mechanism was searched considering to Freundlich, Langmuir, BET and Temkin isotherm model, and the experimental adsorption values were conformed to Freundlich adsorption model. The optimum experimental conditions were investigated as pH 3.5, particle size of 0.125–0.25 mm, stirring speed of 200 rpm, biosorbent concentration of 7 g L−1 and 25 °C. In these conditions, the highest efficiency of biosorption was obtained as 94.07% and after the activating process the efficiency was reached to 97.73% at 70 mg L−1. The maximum Pb (II) removal capacity of raw tea factory waste was found to be 22.111 mg g−1 at 200 mg L−1. The biosorption kinetics has complied with the pseudo-second-order model. Thermodynamic studies stated that this biosorption phenomenon was an endothermic process.

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  AtıfScopus26·WoS26·OpenAlex27

  İncele
• MakaleAçık Erişim2019Scopus SJRQ2/r/bayburt/13157
  Effective reduction of graphene oxide using sulfur dioxide-containing chemical compounds

  Korucu, H.; Şimşek, B.; Kocakerim, M.M.; Karakaş, I.H.

  The success of the graphene oxide reduction process depends on how similar the product is to pristine graphene. Sulfur oxide, which is a significant industrial waste gas, can be used in the reduction of graphene oxide. In this study, the graphene oxide reduction process was performed by using sulfur oxide with sodium tetraborate decahydrate, l-ascorbic acid, ammonium hydroxide, sodium hydroxide, lithium hydroxide, sodium borohydride and sodium thiosulfate. The carbon-to-oxygen atomic ratio and D-to-G peak ratio of the graphene oxide, which represent the degree of reduction, were 2.64–4 and 0.78–1.80 with the use of sulfur oxide, respectively. The sulfur oxide/sodium borohydride mixture increased the carbon-to-oxygen atomic ratio of the graphene oxide to 11.73, while improving the value of the D-to-G peak ratio at 3.14. The reduced graphene oxide with the highest specific heat capacity was obtained using sodium tetraborate decahydrate, with an improvement of 74.54% compared to graphene oxide. The results show that sulfur oxide, which is harmful to the environment and human health, can be utilized in an effective reduction process, together with other reducing chemicals, to obtain an industrially valuable material, such as reduced graphene oxide.

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  AtıfScopus15·WoS14·OpenAlex15

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