Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 7Citation - Scopus: 7Hydrogen Production From Energetic Poplar and Waste Sludge by Electrohydrogenesis Using Membraneless Microbial Electrolysis Cells(Pergamon-elsevier Science Ltd, 2024) Goren, A. Yagmur; Kilicaslan, A. Faruk; Dincer, Ibrahim; Khalvati, AliMembraneless microbial electrolysis cells (MECs) are potentially considered to produce biohydrogen (bioH2) in a green manner and simultaneously minimize agricultural and wastewater facility wastes. However, effective, sustainable, and cost-effective system configuration and improvement of operating variables, working at ambient conditions, are needed to make the MEC a sustainable process. Therefore, this study investigates the bioH2 production from poplar leaves and anaerobic sludge mixture by incorporating nanomaterials comprising Al2O3, MgO, and Fe2O3 metal oxides at various dosages. Moreover, the effects of applied cell voltage (0.5-1.5 V) and inoculum amount (20-40 mL) on bioH2 production and organic matter removal performance are evaluated. The maximum bioH2 production value is 417 mL at an applied voltage of 1.5 V with a chemical oxygen demand (COD) removal efficiency of 37.6 % under operating times of 5 min using 40 ml of inoculum. The bioH2 production of the MEC system is reduced with the decrease in inoculum amount. The highest bioH2 production of 828 mL is obtained at improved conditions in the presence of 1 g of Fe2O3 metal oxide. Overall, this study provides the potentiality of simultaneous waste minimization and bioH2 production under ambient conditions that highlight the waste-to-energy pathway for membraneless and green bioelectrochemical process.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 LLCBook Part Citation - Scopus: 1Biomass-Based Polygeneration Systems With Hydrogen Production: a Concise Review and Case Study(Springer Science and Business Media Deutschland GmbH, 2024) Hajimohammadi Tabriz,Z.; Mohammadpourfard,M.; Gökçen Akkurt,G.; Çağlar,B.This chapter discusses the importance of biomass-based polygeneration systems in producing hydrogen as a clean and safe energy carrier. The benefits of polygeneration systems, which can produce multiple products and minimize waste, are highlighted, and the need for clean and efficient hydrogen production is emphasized. This study gives a brief overview of hydrogen production from biomass-based polygeneration systems, which examines the systems in two main classifications: systems that use biomass as a potential and rich source of hydrogen and systems that exploit the energy content of biomass to run hydrogen production units. Furthermore, a new multigeneration system with hydrogen production has been introduced and thermodynamically evaluated. Also, its results have been obtained in a real situation. Overall, this chapter offers insights into the potential of biomass-based polygeneration systems in meeting energy demands while reducing environmental impact. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Article Citation - WoS: 4Citation - Scopus: 5Experimental Investigation of a Unique Electro-Biomembrane Based Integrated System for Wastewater Treatment and Simultaneous Clean Water, Hydrogen and Energy Production(Institution of Chemical Engineers, 2024) Goren,A.Y.; Dincer,I.; Khalvati,A.This paper concerns the design, development, and building of a unique electro-bio-membrane reactor for concurrent bioH2 production, desalination, and energy production by microorganisms in a single reactor. The effects of varying biomass amounts (5–50 g) and inoculum amounts (250–1500 mL) on the bioH2 production efficiency are also investigated. The lowest cumulative bioH2 yield of 24.2 mL/g is obtained using a biomass amount of 5 g, while it is 44.7 mL/g at a biomass amount of 50 g. The highest H2 production from water electrolysis is also found as 0.719 mL/min at improved conditions. Furthermore, the highest power and current density values are 2794.5 mW/m2 and 2786.1 mA/m2 at 1500 mL-inoculum, biomass amount of 30 g, initial pH of 5.5, and temperature of 37 °C in the dark fermentation (DF) cell. Moreover, the desalination efficiency increases from 41.6 to 65.8% with decreasing inoculum amounts from 1500 to 250 mL. © 2024 The Institution of Chemical Engineers