Orak, Ceren
Loading...
Profile URL
Name Variants
Job Title
Email Address
Main Affiliation
01. Izmir Institute of Technology
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
1NO POVERTY
0
Research Products
2ZERO HUNGER
1
Research Products
3GOOD HEALTH AND WELL-BEING
0
Research Products
4QUALITY EDUCATION
0
Research Products
5GENDER EQUALITY
0
Research Products
6CLEAN WATER AND SANITATION
6
Research Products
7AFFORDABLE AND CLEAN ENERGY
11
Research Products
8DECENT WORK AND ECONOMIC GROWTH
1
Research Products
9INDUSTRY, INNOVATION AND INFRASTRUCTURE
2
Research Products
10REDUCED INEQUALITIES
0
Research Products
11SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
12RESPONSIBLE CONSUMPTION AND PRODUCTION
1
Research Products
13CLIMATE ACTION
4
Research Products
14LIFE BELOW WATER
1
Research Products
15LIFE ON LAND
2
Research Products
16PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
17PARTNERSHIPS FOR THE GOALS
0
Research Products
Documents
30
Citations
304
h-index
12
Documents
0
Citations
0
Scholarly Output
17
Articles
14
Views / Downloads
40545/2011
Supervised MSc Theses
0
Supervised PhD Theses
1
WoS Citation Count
180
Scopus Citation Count
189
Patents
0
Projects
0
WoS Citations per Publication
10.59
Scopus Citations per Publication
11.12
Open Access Source
7
Supervised Theses
1
| Journal | Count |
|---|---|
| Turkish Journal of Chemistry | 3 |
| International Journal of Hydrogen Energy | 2 |
| ChemistrySelect | 2 |
| ACS Omega | 2 |
| International Journal of Energy Research | 1 |
Current Page: 1 / 3
Scopus Quartile Distribution
Competency Cloud
17 results
Scholarly Output Search Results
Now showing 1 - 10 of 17
Article Citation - WoS: 16Citation - Scopus: 17Integrating Experimental and Machine Learning Approaches for Predictive Analysis of Photocatalytic Hydrogen Evolution Using Cu/G-c3n4(Pergamon-elsevier Science Ltd, 2024) Arabaci, Bahriyenur; Bakir, Rezan; Orak, Ceren; Yuksel, AsliThis study addresses environmental issues like global warming and wastewater generation by exploring waste-toenergy strategies that produce renewable hydrogen and treat wastewater simultaneously. Cu/g-C3N4 is used to evolve hydrogen from sucrose solution and the impact of reaction parameters such as pH (3, 5, and 7), Cu loading (5, 10, and 15 wt%), catalyst amount (0.1, 0.2, and 0.3 g/L), and oxidant (H2O2) concentration (0, 10, and 20 mM) on the evolved hydrogen amount is examined. Characterization study confirmed successful incorporation of Cu without significantly altering g-C3N4 properties. The highest hydrogen production (1979.25 mu mol g- 1 & sdot;h- 1) is achieved with 0.3 g/L catalyst, 20 mM H2O2, 5 % Cu loading, and pH 3. The experimental study concludes that Cu/g-C3N4 is an effective photocatalyst for renewable hydrogen production. In addition to the experimental investigations, various machine learning (ML) models, including Random Forest, Decision Tree, XGBoost, among others, are employed to analyze the impact of reaction parameters and forecast the quantities of produced hydrogen. Alongside these individual models, an ensemble approach is proposed and utilized. The R2 values of these ML models ranged from 0.9454 to 0.9955, indicating strong predictive performance across the board. Additionally, these models exhibited low error rates, further confirming their reliability in predicting hydrogen evolution.Article Citation - WoS: 52Citation - Scopus: 57Optimizing Hydrogen Evolution Prediction: a Unified Approach Using Random Forests, Lightgbm, and Bagging Regressor Ensemble Model(Elsevier Ltd, 2024) Bakır,R.; Orak,C.; Yüksel,A.Hydrogen, as a clean and versatile energy carrier, plays a pivotal role in addressing global energy challenges and transitioning towards sustainable energy systems. This study explores the convergence of machine learning (ML) for photocatalytic hydrogen evolution from sucrose solution using perovskite-type catalysts, namely LaFeO3 (LFO) and graphene-supported LaFeO3 (GLFO). This study pioneers the practical application of ML techniques, including Random Forests, LightGBM, and Bagging Regressor, to predict hydrogen yields in the presence of these photocatalysts. LFO and GLFO underwent a thorough characterization study to validate their successful preparation. Noteworthy, the highest hydrogen yield from the sucrose model solution was achieved using GLFO as 3.52 mmol/gcat. The optimum reaction conditions were experimentally found to be pH = 5.25, 0.15 g/L of catalyst amount, and 7.5 mM of HPC (hydrogen peroxide concentration). A pivotal contribution of this research lies in the practical application of ML models, culminating in the development of an ensemble model. This collaborative approach not only achieved an overall R2 of 0.92 but also demonstrated exceptional precision, as reflected in remarkably low error metrics. The mean squared logarithmic error (MSLE) was 0.0032, and the mean absolute error (MAE) was 0.049, underscoring the effectiveness of integrating diverse ML algorithms. This study advances both the understanding of photocatalytic hydrogen evolution and the practical implementation of ML in predicting intricate chemical reactions. © 2024 Hydrogen Energy Publications LLCArticle Citation - WoS: 11Citation - Scopus: 12Treatment of Sugar Industry Wastewater by Using Subcritical Water as a Reaction Media(Wiley, 2023) Orak, Ceren; Öcal, Bulutcem; Yüksel, AslıThe sugar industry is one of the most wastewater-producing industries and it contains high content of organic and inorganic substances. Treating and reusing wastewater has significant importance because sugar industry needs to use a high volume of water. In this study, sugar industry wastewater was treated under subcritical conditions and the impacts of reaction temperature and duration over TOC removal percentage were investigated. Additionally, the impact of NaOH concentration over TOC removal percentage was examined. The highest TOC removal was obtained almost 95 % in the presence of 0.1 M of NaOH at 240 degrees C for 90 min of reaction duration. Treatment of sugar industry wastewater by subcritical water oxidation followed the second-order reaction kinetic model and the activation energy was found as 11.41 kJ/mol. Furthermore, the intermediate products were identified via GC-MS.Article Citation - WoS: 13Citation - Scopus: 12Comparison of Photocatalytic Performances of Solar-Driven Hybrid Catalysts for Hydrogen Energy Evolution From 1,8–diazabicyclo[5.4.0]undec-7 (dbu) Solution(Elsevier, 2022) Orak, Ceren; Yüksel, AslıHydrogen is evolved from 1,8–Diazabicyclo [5.4.0]undec-7-ene (DBU) model solution which is a nitrogen-containing heterocyclic organic compound using different solar-driven hybrid photocatalysts. A characterization study is performed and the results of PL analysis show that the most promising solar-driven hybrid catalyst is graphene supported LaFeO3. Then, an experimental design matrix is built using the Box Behnken model to main and interaction effects of reaction parameters (pH, catalyst loading, and [H2O2]0). Based on the experimental results relatively higher hydrogen amounts are achieved using GLFO and this finding is supported by PL analysis. The highest hydrogen amount and DBU removal are determined as 3058.31 μmol/gcat and 90.3%, respectively. Statistical analysis shows that the square of catalyst loading is the only effective parameter over the produced hydrogen amount from the DBU model solution using GLFO and the R2 of model is 92.47%. Thus, hydrogen production and wastewater treatment could be achieved via photocatalytic oxidation as concomitant.Article Citation - WoS: 1Citation - Scopus: 1Selective Catalytic Hydrogenation of Cellulose Into Sorbitol With Ru-Based Catalysts(TÜBİTAK, 2022) Orak, Ceren; Sapmaz, Aycan; Yüksel, AslıSorbitol is one of the platform chemicals and can be produced from various renewable and sustainable sources via different processes. Hydrothermal liquefaction is an effective and promising approach to produce sorbitol, since the subcritical reaction media and appropriate catalysts provide a selective production of platform chemicals. In this study, sorbitol was produced from different renewable sources (cellulose and glucose) in the presence of Ru-based catalysts (Ru/SiO2, Ru/AC, Ru/SBA-15, and Ru/SBA-15-SO3) under subcritical conditions. The highest cellulose conversion was achieved as 90% in the presence of Ru/SBA-15-SO3 for 1 h of reaction duration. The highest sorbitol yield (%) by hydrothermal liquefaction of cellulose was obtained as 6.2% by using Ru/AC for 1 h of reaction duration. A total of 99.9% of glucose conversion was achieved in the presence of all catalysts. The highest sorbitol yield (%) by hydrothermal liquefaction of glucose was found as 3.8% for 1 h of reaction duration. Owing to the results of GC-MS analysis, the intermediate products were identified, and, thus, a reaction pathway was proposed.Article Citation - WoS: 2Citation - Scopus: 2Electrolytic Oxidation of 1,8-Diazabicyclo[5.4.0]undec in Hot-Compressed Water on a Titanium Electrode(American Chemical Society, 2020) Orak, Ceren; Yüksel Özşen, AslıThe nitrogen-containing heterocyclic organic compound, 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU), was chosen to prepare a model solution to represent nitrogen-containing industrial waste streams. A hybrid reactor system was designed to combine electrolysis with wet oxidation in hot compressed water using a titanium electrode. The effects of current density, NaOH concentration, and reaction time on DBU and total organic carbon (TOC) removal were investigated via Minitab 18 software to clarify the main and interaction effects. Statistical analysis shows that the NaOH concentration and current density had significant effects on DBU removal. The highest DBU (91.2%) and TOC (45%) removal was observed at the lowest DBU concentration (3 mM) for 90 min of reaction time. Last, the effect of temperature on DBU and TOC removal was investigated. TOC removal was described with the first-order reaction kinetic model. Rate constants were determined as 0.0025, 0.041, and 0.050 min(-1) at 200, 240, and 280 degrees C, respectively. The activation energy was calculated as 79.86 kJ/mol.Article Citation - WoS: 14Citation - Scopus: 12Photocatalytic Hydrogen Energy Evolution From Sugar Beet Wastewater(Wiley-VCH Verlag, 2021) Orak, Ceren; Yüksel, AslıHydrogen is a clean, environmentally friendly, storable, and sustainable green energy source as well as a potential fuel. It could be produced from various biomass, wastewater, or other sources by different processes. In this study, hydrogen was evolved from sucrose model solution and real sugar beet wastewater by photocatalytic oxidation using a perovskite catalyst under solar light irradiation. In this context, firstly, the graphene supported LaFeO3 (GLFO) was synthesized and then, a characterization study shows that GLFO is successfully synthesized. To optimize the reaction parameters (pH, catalyst loading, and initial hydrogen peroxide concentration), an experimental matrix was created using the Box Behnken model. Whereas the highest hydrogen evolution from sucrose model solution was observed as 3520 μmol/gcat, the highest hydrogen evolution from sugar beet wastewater was obtained as 7035 μmol/gcat. The highest TOC removal (99.73 %) from sugar beet wastewater was also achieved at the same reaction conditions.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: 10Citation - Scopus: 12Novel Hybrid Adsorption-Electrodialysis (aded) System for Removal of Boron From Geothermal Brine(American Chemical Society, 2022) Altınbaş, Bekir Fırat; Orak, Ceren; Ökten, Hatice Eser; Yüksel, AslıA novel hybrid adsorption-electrodialysis (AdED) system to remove environmentally harmful boron from geothermal brine was designed and effective operating parameters such as pH, voltage, and flow rate were studied. A cellulose-based adsorbent was synthesized from glycidyl methacrylate (GMA) grafted cellulose and modified with a boron selective n-methyl-d-glucamine (NMDG) group and characterized with SEM-EDX, FT-IR, and TGA analyses. Batch adsorption studies revealed that cellulose-based adsorbent showed a remarkable boron removal capacity (19.29 mg/g), a wide stable operating pH range (2-10), and an adsorption process that followed the Freundlich isotherm (R2= 0.95) and pseudo-second-order kinetics (R2= 0.99). In the hybrid AdED system, the optimum operating parameters for boron removal were found to be a pH of 10, a voltage of 10 V, a flow rate of 100 mL/min, and an adsorbent dosage of 4 g/L. The presence of the adsorbent in the hybrid system increased boron removal from real geothermal brine (containing 199 ppm boron) from 7.2% to 73.3%. The results indicate that the designed AdED system performs better than bare electrodialysis for boron removal from ion-rich real geothermal brine while utilizing environmentally friendly cellulose-based adsorbent.Article Selective Catalytic Hydrogenation of Cellulose Into Sorbitol With Ru-Based Catalysts(Tubitak Scientific & Technological Research Council Turkey, 2022) Orak, Ceren; Sapmaz, Aycan; Yüksel Özsen, AslıSorbitol is one of the platform chemicals and can be produced from various renewable and sustainable sources via different processes. Hydrothermal liquefaction is an effective and promising approach to produce sorbitol, since the subcritical reaction media and appropriate catalysts provide a selective production of platform chemicals. In this study, sorbitol was produced from different renewable sources (cellulose and glucose) in the presence of Ru-based catalysts (Ru/SiO2, Ru/AC, Ru/SBA-15, and Ru/SBA-15-SO3) under subcritical conditions. The highest cellulose conversion was achieved as 90% in the presence of Ru/SBA-15-SO3 for 1 h of reaction duration. The highest sorbitol yield (%) by hydrothermal liquefaction of cellulose was obtained as 6.2% by using Ru/AC for 1 h of reaction duration. A total of 99.9% of glucose conversion was achieved in the presence of all catalysts. The highest sorbitol yield (%) by hydrothermal liquefaction of glucose was found as 3.8% for 1 h of reaction duration. Owing to the results of GC-MS analysis, the intermediate products were identified, and, thus, a reaction pathway was proposed.