Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Book Part Waste to Energy Management(Elsevier, 2025) Yagmur Goren, A.Y.; Kalinci, Y.; Dincer, I.Today, the world faces growing challenges with waste problems since people have moved the problems from past to future. The key question is: is waste a problem or a resource? The correct response to this question can be found by investigating, in more detail, the types of waste and implemented waste management methods. The chapter consists of six main sections. The first section is focused on classification, which explains what waste is and categorizes it according to the producer (e.g., municipal, industrial, and hazardous) and chemical composition (for instance, organic, inorganic, and microbiological). The second section presents legislative trends. It is seen that the waste management legislations are changing from country to country. Also, it can change over time because every technological development emerges its waste. The third section covers waste management methods such as recycling, refuse-derived fuel, landfill, and thermal methods. The landfill method is the oldest and the cheapest one. It is seen that the method will continue in the near future, too, though a lot of legal regulations have been made to reduce its usage. Thermal methods are commonly used in the industrial sector. Hence, thermal methods such as incineration, pyrolysis, and gasification are examined in detail. Considering environmental issues, thermal technology moves toward gasification systems to reduce greenhouse gas emissions and the formation of by-products. The fourth section presents illustrative examples related to using waste management methods or their combinations. Further, a case study, which consists of a circulated fluidized bed gasification system, is investigated from the exergy and exergoeconomic points of view. The chapter presents exergy and exergoeconomic analyses in detail. The analyses show that it can produce 1.17 MWe power and 0.521kg/s hydrogen with 3.33 $/kg cost from 8.5kg/s biomass waste. Finally, future scenarios for waste management are investigated. Also, to achieve zero waste targets in the future, circular economy and industrial symbiosis concepts are examined, and some successful examples from around the world are presented. © 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.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: 7Citation - Scopus: 6A Literature Review on Sustainable Buildings and Neighborhoods in Terms of Daylight, Solar Energy and Human Factors(Elsevier, 2025) Cogul, Ilgin cataroglu; Kazanasmaz, Zehra Tugce; Ekici, BerkSustainability has become the focus and interest of researchers with climate change's increasing impact and challenges. Considering various perspectives, published studies focus on sustainability in architecture and the built environment, such as using daylight more effectively, enhancing energy efficiency, and designing nearly zero-energy buildings. Given the attention to sustain- ability in this domain, this review assesses the abovementioned viewpoints in buildings regarding environmental factors in relation to the micro and macro scales of the buildings and neighborhoods. Human factor has increasingly been of interest in recent works of sustainable environments. This study identifies the gaps with respect to architectural design elements considering daylighting, energy efficiency and human factors on building and neighborhood scales. A comprehensive table of the reviewed studies summarizes the aim, methodology, optimization algorithm, objective function, machine learning algorithm, digital tools, location, independent and dependent variables, view, wellness, well-being, daylight/energy performance metrics, scale, and solar strategy. The results showed that the current state-of-the-art focus on energy efficiency mainly considers passive design strategies at the building scale. Studies in the daylight domain primarily consider window properties, shading devices, and orientation. Human-centric studies showed that daylighting improves the emotional well-being of building occupants but can have negative effects such as overheating and glare. Overall findings emphasize the necessity of a holistic approach in achieving sustainability goals in dwellings at the building and neighborhood scale.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: 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.Book 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 - 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.