Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Machine Learning Integrated Solvothermal Liquefaction of Lignocellulosic Biomass to Maximize Bio-Oil Yield(Elsevier Sci Ltd, 2025) Ocal, Bulutcem; Sildir, Hasan; Yuksel, AsliAccelerating consumption of limited fossil-based for economic growth and simultaneously mitigating greenhouse gas emissions create a dilemma that is waiting to be solved by researchers. In this context, solvothermal liquefaction of lignocellulosic biomass to produce bio-oil is a promising way to obtain green energy. However, maximizing bio-oil is challenging to optimize the operating parameters employing conventional techniques due to the complexity and non-linearity of the process. Lately, machine learning approaches have become powerful tools for addressing complex nonlinear problems by predicting process behavior and regulating operating parameters for optimization by learning from datasets. The current research demonstrates integrating experimental and a developed artificial neural network model to optimize solvothermal liquefaction of pinus brutia, based on temperature, water fraction, and biomass amount in maximizing bio-oil generation for the first time. The highest bio-oil yields were obtained at 31.40 %, 18.68 %, and 39.69 %, respectively, with 4 and 8 g biomass in the presence of water, ethanol, and water/ethanol mixture at 240 degrees C. Under the model conditions, the maximum biooil yield was experimentally verified at 46.20%, which was predicted at 48.8 %. Beyond providing accurate yield predictions, the approach highlights the potential of date-driven modeling to reduce experimental workload and cost while aiding parameter selection to improve efficiency. These outcomes emphasize the importance of machine learning integration into liquefaction process, providing remarkable results for future process design, optimization, and scalability. On the other hand, the study also includes characterization results (ultimate, proximate, FTIR, and GC-MS) of selected products and pinus brutia.Article Citation - WoS: 5Citation - Scopus: 5Nanoarchitectonics Approach To Graphite/Starch-supported Bioelectrode for Enhanced Supercapacitor Performance(Elsevier, 2025) Goren, Aysegul Yagmur; Dincer, IbrahimThere has been an increasing interest in finding suitable materials for supercapacitor applications in response to the growing need for energy, to use alternative energy sources to fossil fuels in addition to energy storage. In this regard, bio-based carbon-loaded materials can be a promising option for high-performance supercapacitors because of their abundance, diversity, and reproducibility with waste management strategies. In this study, a new graphite-loaded bioelectrode is synthesized for supercapacitor application. The electrochemical performance of the synthesized electrode is tested at room temperature using the cyclic voltammetry method, and the capacity and energy density of the electrodes are evaluated. The electrochemical performance of 1 g of graphiteloaded bioelectrode was 3.5 mA/cm2, while the specific capacitance value was 355.6 F/g at a current density of 0.5 A/g. Furthermore, the bioelectrode provided significant cyclic stability with 93.5% in specific capacitance value after 5000 charge/discharge cycles at the current density of 0.5 A/g. Consequently, the synthesized bioelectrode can be a promising option for energy storage as a sustainable electrode due to its superior conductivity, stability, and low cost.Article Citation - WoS: 6Citation - Scopus: 6A New Electro-Biomembrane Integrated Renewable-Based System To Produce Power, Fresh Water and Hydrogen for Sustainable Communities(Elsevier, 2025) Goren, A. Yagmur; Dincer, Ibrahim; Khalvati, AliAs the consequences of global warming become more severe, it is more crucial than ever to capitalize on all locally accessible potential renewable energy sources and produce sufficient useable energy outputs to meet community demands while causing the least damage to the ecosystem. Therefore, this paper focuses on a unique parabolic trough collector solar system-powered electro-biomembrane unit that combines a heat and power system with fresh water, electricity and hydrogen production. The proposed integrated system contains the following subsystems: a combining parabolic trough collector solar system, an organic Rankine cycle, a steam Rankine cycle, a multi-stage flash desalination system, and an electro-biomembrane H2 and freshwater production system. A thorough analysis and parametric research are performed on the multigeneration system to determine how important characteristics affect system performance and evaluate the energy and exergy efficiencies, and exergy destruction levels for particular system elements. The study results show that solar irradiation is the most critical parameter for improving system performance. The highest freshwater production of 1,303,333.3 L/day is observed at the solar irradiation of 935,768 kWh/day. Furthermore, the combined output of three electricity production technologies exceeds 2,000,000 kWh/day, highlighting the ability of the system to harness solar thermal energy effectively. The study findings indicate that using solar power and biomass as renewable energy sources, the proposed integrated system provided 328.56 kg of biohydrogen per day. Overall, the energy and exergy efficiencies of the integrated system are obtained as 34.3 and 29.5 %, respectively.Article Citation - WoS: 10Citation - Scopus: 10The Role of Effective Catalysts for Hydrogen Production: a Performance Evaluation(Pergamon-elsevier Science Ltd, 2025) Goren, A. Yagmur; Temiz, Mert; Erdemir, Dogan; Dincer, IbrahimIn recent years, research on hydrogen (H2) production for alternative and environmentally-benign energy solution as fuel, storage medium and feedstock has been one of the most highly demanded subjects. It aims to reduce the pressures set by carbon dioxide emissions and the depletion of fossil fuel supplies. Nevertheless, largescale H2 production is limited by its high cost and low yield. The distinct photo-electrochemical characteristics of catalysts have shown them to have great promise for enhancing the production of H2. This article presents an updated and comprehensive review of enhanced H2 production using various catalysts in biological, thermochemical, and water-based processes. Various operational parameters (reactor configuration, catalyst dosage, catalyst type, catalyst modification methods, temperature, pH, and inoculum type) are summarized to improve the H2 production performance and reduce the environmental impacts and costs of these processes. For instance, in dark fermentation, biological H2 production is enhanced by 3.2-38 % with certain metal catalysts. Overall, results revealed that catalysts, specifically inorganic catalysts such as iron, nickel, titanium oxide, and silver, have improved the production rate of H2. This review has provided the application fields and working principles of catalysts in different H2 production processes. Finally, we suggested the main concerns that need to be prioritized in the long-term advancement of H2 production using catalysts.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 - Scopus: 5Event Distortion-Based Clustering Algorithm for Energy Harvesting Wireless Sensor Networks(Springer, 2022) Al-Qamaji, A.; Atakan, B.Wireless sensor networks (WSNs) consist of compact deployed sensor nodes which collectively report their sensed readings about an event to the Base Station (BS). In WSNs, due to the dense deployment, sensor readings can be spatially correlated and it is nonessential to transmit all their readings to the BS. Therefore, for more energy efficient, it is vital to choose which sensor node should report their sensed readings to the BS. In this paper, the event distortion-based clustering (EDC) algorithm is proposed for the spatially correlated sensor nodes. Here, the sensor nodes are assumed to harvest energy from ambient electromagnetic radiation source. The EDC algorithm allows the energy-harvesting sensor nodes to select and eliminate nonessential nodes while maintain an acceptable level of distortion at the BS. To measure the reliability, a theoretical framework of the distortion function is first derived for both single-hop and two-hop communication scenarios. Then, based on the derived theoretical framework, the EDC algorithm is introduced. Through extensive simulations, the performance of the EDC algorithm is evaluated in terms of achievable distortion level, number of alive nodes and harvested energy levels. As a result, EDC algorithm can successfully exploit both the spatial correlation and energy harvesting to improve the energy efficiency while preserving an acceptable level of distortion. Furthermore, the performance comparisons reveal that the two-hop communication model outperforms the single-hop model in terms of the distortion and energy-efficiency. © 2021, The Author(s).Conference Object Citation - Scopus: 1Daylight Performance and Lighting Energy Savings of Amorphous and Crystalline Silicon Solar Cells in an Architecture Studio(IEEE, 2023) Taşer, Aybüke; Kazanasmaz, Zehra TuğçeSemi-transparent photovoltaic (PV) glass increased its popularity due to its energy and environmental advantages, which can generate electricity on-site and utilize natural daylight. They use thin-film solar cells to allow daylight to enter space and generate electrical energy. Crystalline and amorphous silicon (a-Si) solar cells are the most prominent in literature and industry due to their high efficiency and sufficient transparency. This study aims to assess the daylight and lighting energy-saving potential of thin-film crystalline and a-Si photovoltaic glass in an architecture studio in Izmir, Turkey. The simulation engine applied two types of solar cells on existing windows to evaluate the advantage of such glass for daylight performance and lighting energy consumption. Spatial Daylight Autonomy (sDA), a climate-based annual daylight performance metric, evaluates the daylight performance of the studio. Research findings note that such solar cells enhance the visual comfort of occupants and the daylight performance of the studio. In addition, crystalline silicon solar cells can cover the studio's whole lighting loads in the summer and fall seasons and balance them up to 66% and 23% in the spring and winter seasons, respectively. These have higher transmittance and peak power, thus; resulting in higher energy and daylight performance. © 2023 IEEE.