Chemical Engineering / Kimya Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/14
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Article Citation - WoS: 15Citation - Scopus: 16A Machine Learning Ensemble Approach for Predicting Solar-Sensitive Hybrid Photocatalysts on Hydrogen Evolution(IOP Publishing, 2024) Bakır, Rezan; Orak, Ceren; Yuksel, AsliHydrogen, as the lightest and most abundant element in the universe, has emerged as a pivotal player in the quest for sustainable energy solutions. Its remarkable properties, such as high energy density and zero emissions upon combustion, make it a promising candidate for addressing the pressing challenges of climate change and transitioning towards a clean and renewable energy future. In an effort to improve efficiency and reduce experimental costs, we adopted machine learning techniques in this study. Our focus turned to predictive analyses of hydrogen evolution values using three photocatalysts, namely, graphene-supported LaFeO3 (GLFO), graphene-supported LaRuO3 (GLRO), and graphene-supported BiFeO3 (GBFO), examining their correlation with varying levels of pH, catalyst amount, and H2O2 concentration. To achieve this, a diverse range of machine learning models are used, including Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), XGBoost, Gradient Boosting, and AdaBoost-each bringing its strengths to the predictive modeling arena. An important step involved combining the most effective models-Random Forests, Gradient Boosting, and XGBoost-into an ensemble model. This collaborative approach aimed to leverage their collective strengths and improve overall predictability. The ensemble model emerged as a powerful tool for understanding photocatalytic hydrogen evolution. Standard metrics were employed to assess the performance of our ensemble prediction model, encompassing R squared, Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and Mean Absolute Error (MAE). The yielded results showcase exceptional accuracy, with R squared values of 96.9%, 99.3%, and 98% for GLFO, GBFO, and GLRO, respectively. Moreover, our model demonstrates minimal error rates across all metrics, underscoring its robust predictive capabilities and highlighting its efficacy in accurately forecasting the intricate relationships between GLFO, GBFO, and GLRO values and their influencing factors.Article Citation - WoS: 11Citation - Scopus: 12Box-Behnken Design for Hydrogen Evolution From Sugar Industry Wastewater Using Solar-Driven Hybrid Catalysts(American Chemical Society, 2022) Orak, Ceren; Yüksel, AslıHydrogen is a clean and green fuel and can be produced from renewable sources via photocatalysis. Solar-driven hybrid catalysts were synthesized and characterized (scanning electron microscopy (SEM), transmission electron microscopy (TEM), Brunauer-Emmett-Teller (BET), X-ray diffraction (XRD), photoluminescence (PL) spectroscopy, and UV-vis diffuse reflectance spectroscopy (DSR)), and the results implied that graphene-supported LaRuO3is a more promising photocatalyst to produce hydrogen and was used to produce hydrogen from sugar industry wastewater. To investigate the main and interaction effects of reaction parameters (pH, catalyst amount, and [H2O2]0) on the evolved hydrogen amount, the Box-Behnken experimental design model was used. The highest hydrogen evolution obtained was 6773 μmol/gcatfrom sugar industry wastewater at pH 3, 0.15 g/L GLRO, and 15 mM H2O2. Based on the Pareto chart for the evolved hydrogen amount using GLRO, among the main effects, the only effective parameter was the catalyst amount for the photocatalytic hydrogen evolution from sugar industry wastewater. In addition, the squares of pH and two-way interaction of pH and [H2O2]0were also statistically efficient over the evolved hydrogen amount.Article Citation - WoS: 3Citation - Scopus: 5Adsorption Characteristics of Lead-, Barium- and Hydrogen-Rich Clinoptilolite Mineral(SAGE Publications Inc., 2003) Çakıcıoğlu Özkan, Seher Fehime; Ülkü, SemraThe carbon dioxide and water vapour adsorption properties of local clinoptilolite-rich material, both as the original and as lead-, barium- and hydrogen-rich forms, were examined. The lead- and barium-rich forms were prepared by treatment of the original clinoptilolite with Pb(NO3)2 and BaCl2 respectively, while the hydrogen-rich form was prepared by NH4Cl and heat treatment. Water and CO2 adsorption experiments were conducted in a volumetric system under static conditions, with low-pressure adsorption data being used for the characterization of the natural, Pb-rich, Ba-rich and H-rich clinoptilolite samples. Although the existence of barium-exchange was not noted, an appreciable decrease in CO2 adsorption was observed with the Pb-rich and H-rich forms due to a decrease in the electrostatic interaction between the surface and the adsorbate. Application of the Dubinin-Astakhov equation to the water adsorption data established the existence of micropores of different sizes that exhibited different adsorption mechanisms.Article Citation - WoS: 11Citation - Scopus: 14Effect of Pretreatment on the Performance of Metal-Contaminated Fluid Catalytic Cracking (fcc) Catalysts(Elsevier Ltd., 2004) Bayraktar, Oğuz; Kugler, Edwin L.Effects of both hydrogen and methane pretreatment on the performance of metal-contaminated equilibrium fluid catalytic cracking (FCC) catalysts from a refinery were investigated. Both hydrogen and methane pretreatment at 700°C were proven to be advantageous since the yields of hydrogen and coke from sour imported gas oil (SIHGO) cracking decrease while light cycle oil (LCO) and gasoline yields increase. The catalysts pretreated with hydrogen have shown slightly better improvement than the catalysts pretreated with methane. The decrease in the yields of hydrogen and coke was attributed to decrease in the dehydrogenation activity of vanadium oxides, which are present at high concentrations on the equilibrium FCC catalysts. This decrease in dehydrogenation activity after the pretreatment was also confirmed by low hydrogen-to-methane ratio. It was found that reduced vanadium has lower dehydrogenation activity since it produces less coke and hydrogen compared to oxidized vanadium. Hydrogen transfer reactions were evaluated by measuring C4 paraffin-to-C4 olefin ratios. Hydrogen transfer reactions decreased with increasing metal concentration. Both hydrogen and methane pretreatment caused the hydrogen transfer reactions to increase. Improved hydrogen transfer reactions caused an increase in the gasoline range products.