WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article Citation - WoS: 4Citation - Scopus: 4Unveiling the Bi-Functional Potential of Cowo4 Hybridized With Tubular G-C3n4 for Highly Photocatalytic Hydrogen Production, Water Purification and Supercapacitance Activities(Pergamon-elsevier Science Ltd, 2025) Erdem, Nurseli Gorener; Tuna, Ozlem; Inan, Ece; Caglar, Basar; Ertis, Irem Firtina; Simsek, Esra BilginIn this paper, CoWO4 nanospheres were successfully hybridized with graphitic carbon nitride with tubular morphology (TCN) and the photocatalytic antibiotic degradation, hydrogen evolution and supercapacitor performances were examined in detail. The morphological, structural and optical properties were characterized. The hybrid CoWO4/TCN-2 catalyst showed the highest tetracycline degradation efficiency with the rate constant of 0.0198 min(-1) which was 3.73 and 5.21 times greater than that of CoWO4 and TCN samples, respectively. The rate of photocatalytic hydrogen evolution was found to be 1997 mu mol/g.h for CoWO4/TCN-2 which was 2.03-fold and 1.09-fold higher than of TCN and CoWO4 samples, respectively. Electrochemical analysis revealed that the charge storage in CoWO4, TCN, and CoWO4/TCN electrodes was mainly governed by faradaic processes. All electrodes showed high-rate capability (>85 %), coulombic efficiency (>90 %) and cycle stability (>100 %). While CoWO4 and TCN electrodes show higher redox activities and specific capacitances than CoWO4/TCN composites, this limitation is mitigated by enhanced wettability in CoWO4/TCN electrodes. Notably, the CoWO4/TCN-2 electrode exhibits superior long-term capacitance, surpassing the TCN electrode after 2000 GCD cycles. This work offers new application areas for the metal tungstate/carbon nitride photocatalysts with improved photocatalytic and electrochemical performances.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.