WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
Browse
4 results
Search Results
Now showing 1 - 4 of 4
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.