SDG 7 · Erişilebilir ve Temiz Enerji · SDG · Erzincan Binali Yıldırım Üniversitesi

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ArticleAçık Erişim2025/r/ebyu/19346
Performance, Emissions and Enviroeconomic Assessment of Diesel–Waste Tyre Pyrolysis Oil–n-Butanol Blends in a Single-Cylinder Engine
Demirci, Oğuz Kürşat; Erol, Derviş; Gülcan, Halil Erdi
This study evaluates the performance, emissions and enviroeconomic implications of diesel–waste tyre pyrolysis oil (WTPO)–butanol blends in a single-cylinder, direct-injection diesel engine operated at 1500 rpm across 10–50 Nm. Five fuels were tested: neat diesel (D100), D90T10, D80T20, D80T10B10 and D60T20B20. Relative to D100, oxygenated blends incurred a modest fuel-consumption penalty (peak ≈ +8% BSFC), yet delivered pronounced reductions in incomplete-combustion products: carbon monoxide fell by about 50% at high load with D60T20B20. WTPO-only mixtures increased unburned hydrocarbons, whereas adding 10% butanol suppressed HC. Conversely, nitrogen oxides rose by roughly 15–45%, highest for D60T20B20, while tailpipe CO2 decreased slightly (≈4% at 50 Nm). A simple carbon-pricing lens (€70 t-1 CO₂) indicated a ~4% lower carbon-cost component for D60T20B20 than D100 at high load. Considering these trade-offs, D80T10B10 emerges as the most pragmatic configuration, balancing efficiency with air-quality benefits and moderating the NOx rise. The results support partial substitution of diesel by WTPO and butanol where NOx control (e.g., EGR or calibration) is feasible, coupling local pollutant mitigation with incremental decarbonisation and modest cost gains.
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ArticleAçık Erişim2025/r/ebyu/12189
Investigation of the combined use of diesel and CNG fuels on an HCCI engine using Response Surface Methodology (RSM)
Demirci, Oğuz Kürşat; Çınar, Can; Kocakulak, Tolga
In this study, the effects of the combined use of diesel and Compressed Natural Gas (CNG) fuels on the performance, combustion and emissions were experimentally and statistically investigated in a Homogeneous Charged Compression Ignition (HCCI) engine. Diesel and CNG fuels were used at different ratios between 0% and 80% by mass, and tests were conducted at different engine loads. The experimental procedure was designed using the Response Surface Methodology (RSM) composite central design method. The experimental data were analyzed using MATLAB and entered into the RSM. In order to determine the response parameters predictably, model equations were created, counter graphs were drawn and optimization was carried out. Engine load and CNG ratio, which are the optimum input parameters, were determined as 68.36% and 2.864%, respectively. The response parameter values were obtained as 4.487 bar for Indicated Mean Effective Pressure (IMEP), 39.3% for Indicated Thermal Efficiency (ITE), 255.5 g/kWh for Brake Specific Fuel Consumption (BSFC), 3.343% for Coefficient of Variation of Indicated Mean Effective Pressure (COVIMEP), 0.247% for CO, 191.566 ppm for HC, 579.538 ppm for NOx and 1.393 m-1 for smoke. This study, in which a combined diesel and CNG fueled engine operating in HCCI combustion mode is examined with experimental and statistical methods, will fill an important gap in the literature and provide researchers with a new perspective.
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ArticleYalnız künye2025/r/ebyu/12177
Design, analysis, and implementation of DC-DC boost converter with new active snubber cell
Gecmez, Hilal Sebnem; Ting, Naim Suleyman; Sahin, Yakup
In this paper, a new active snubber cell for DC-DC boost converters is introduced for the purpose of soft switching. The introduced snubber cell ensures lossless turning-on by zero-voltage transition (ZVT) and turning-off by zero-voltage switching (ZVS) of the main switch. Besides, it enables turning-on by ZVS and turning-off by zero current switching (ZCS) of the main diode. None of the semiconductor power devices are subjected to extra voltage stress, and all of them operate by soft switching (SS). The converter can successfully maintain the SS even under light loads. Furthermore, the proposed converter structure is advantageous in terms of simplicity and low cost. The operating modes and theoretical analysis of the introduced converter are presented and it is validated using a prototype with a 500 W output power and at the 100 kHz switching frequency. Owing to the proposed active snubber cell, the converter efficiency is achieved as 97.2%.
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Book ChapterYalnız künye2025/r/ebyu/12118
An In-depth Analysis of the Energy and Exergy Performance of Radiant Heating Integrated with Ground Source Heat Pumps in Building Environments
Dogan, Ahmet; Kayaci, Nurullah; Demir, Hakan
Addressing global priorities such as energy conservation, the reduction of fossil fuel consumption, and the urgent need to combat climate change is of paramount importance. One promising way to achieve these objectives is the exploration of radiant heating and cooling (RHC) systems as alternatives to conventional building climate systems. RHC systems hold the potential to make substantial contributions to both energy efficiency and the enhancement of indoor thermal comfort. RHC systems have garnered attention for their capacity to not only provide an acceptable level of thermal comfort but also their alignment with renewable energy sources. In this study, a comprehensive analysis of energy and exergy performance was undertaken in a building environment. This environment was equipped with a ground source heat pump (GSHP) system linked with radiant panels (RPs). The research was conducted within the confines of the Science and Technology Application and Research Center at YTU. To ensure the precision and reliability of the conducted analyses, a range of critical measurements were taken. These measurements encompassed parameters such as the input and output temperatures of both the ground and panel water, power consumption data for all the equipment within the heat pump (HP) system, and recordings of indoor and outdoor air temperature values. This meticulous data collection process serves as the foundation for the subsequent comprehensive assessment. Furthermore, as part of this study, measurements were carried out under various configurations of the radiant panels. The objective was to evaluate the system’s exergy destruction and overall performance across different scenarios. By comparing the outcomes of these diverse configurations, the research aims to provide valuable insights into the optimal use and efficiency of RHC systems in real-world applications.
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ArticleYalnız künye2025/r/ebyu/12116
Evaluating membranes for hydrogen storage and utilization in next-generation aviation systems
Ayar, Murat; Cinoglu, Bahadır; Iulianelli, Adolfo; Karakoc, T. Hikmet
This study aims to provide a comprehensive evaluation of membrane technologies for hydrogen-related processes in aviation, specifically focusing on hydrogen production, hydrogen separation, and fuel cells. As aviation seeks to transition to cleaner energy solutions, the selection of appropriate membranes is critical for ensuring efficiency and sustainability. The research utilizes the Analytic Hierarchy Process (AHP) to systematically assess membrane alternatives based on key criteria: economic factors, environmental impact, technical performance, and technological maturity. By conducting pairwise comparisons and detailed matrix calculations, this study establishes the relative importance of sub-criteria and ranks membrane types for each hydrogen-related application. The analysis identifies Nonporous Dense Films as the most effective membrane for hydrogen production, due to their balance of cost and technical performance. For hydrogen separation, Ceramic and Metal Membranes are determined to be the optimal choice, offering superior durability, hydrogen permeability, and thermal stability. In fuel cell applications, Electrically Charged Membranes are found to be the most suitable for Proton Exchange Membrane Fuel Cells (PEMFCs), while Ceramic and Metal Membranes excel in Solid Oxide Fuel Cells (SOFCs). The outcomes of this study not only highlight the most suitable membranes for different aviation hydrogen processes but also offer a strategic framework for decision-makers. By identifying the key factors driving membrane selection, this research contributes to advancing hydrogen adoption in aviation, facilitating the development of efficient, low-emission technologies for the future of sustainable air travel.
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Book ChapterYalnız künye2025/r/ebyu/12073
2D Materials for Solar-Assisted Hybrid Energy Storage Devices: Photo-Supercapacitors
Yesilbag, Yasar Ozkan; Yesilbag, Fatma Nur Tuzluca; Huseyin, Ahmad; Salih, Ahmed Jalal Salih; Ertugrul, Mehmet
Photo-supercapacitors (PSCs) are gaining recognition as a feasible option for future electronic devices and have attracted considerable research attention in recent years. These devices, designed for storing light energy, are viewed as a promising energy source for smart electronics, flexible technologies, and wearable devices. PSCs integrate solar cells with supercapacitors, facilitating the conversion of light energy into electrical energy, which is subsequently stored in chemical energy. Their exceptional light conversion efficiency and outstanding energy storage capabilities distinguish PSCs as key players in light-operated energy storage solutions. Recent studies have extensively explored the application of nanomaterials (1D, 2D, and 3D) as potential electrode materials in these devices. Furthermore, there has been a notable shift toward research to decrease dependence on traditional energy sources. This chapter delves into PSCs’ structure, mechanisms, and operational principles alongside an overview of the available types. It concludes with significant recommendations for improving PSC performance by innovating new materials that exhibit optical and capacitive properties. Additionally, it addresses PSC’s challenges and issues and proposes appropriate solutions.
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ArticleAçık Erişim2025/r/ebyu/11966
Thermal-hydraulic investigation of novel thoriumuranium fuel mixtures in advanced SMR assembly configurations
Uzun, Sinem; Genç, Yasin; Rifai, Hanan; Kabach, Ouadie; Uzun, Bedrettin; Sadoune, Zouhair; Chakir, El Mahjoub; Amsil, Hamid; El Banni, Fadi
Nuclear energy sustainability and deployment flexibility can be significantly enhanced through Small Modular Reactors (SMRs) technology. Critical to their operational success is the thorough assessment of thermal-hydraulic characteristics, especially when incorporating advanced fuel design concepts. This research conducts an extensive thermal-hydraulic analysis examining various thorium-based fuel formulations, including (Th-235 U)O2, (Th-233 U) O2, and an innovative (Th-233 U-235 U)O2 composition, benchmarked against standard UO2 fuel. The investigation encompasses both solid fuel arrangements and dual-cooled annular assembly designs, focusing on safety optimization and operational efficiency enhancement. The analysis focuses on key safety parameters, including pressure drop, coolant enthalpy, fuel centerline temperature, and Departure from Nucleate Boiling Ratio (DNBR). Results for solid fuel configurations reveal that thorium-based fuels exhibit reduced pressure drop, more efficient enthalpy distribution, lower peak fuel temperatures, and higher DNBR values compared to conventional UO2, highlighting improved thermal stability and safety margins. The (Th-233 U-235 U)O2 mixture demonstrates a balanced performance by mitigating the limitations of other thorium compositions. In annular configurations, all fuel types benefit from enhanced heat removal due to the dual cooling surfaces, resulting in further reductions in pressure drop and peak temperatures, as well as a significant increase in DNBR values. The highest DNBR, reaching up to 3.051, confirms the annular geometry’s superior safety performance against boiling crises.
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ArticleYalnız künye2025/r/ebyu/11847
Investigation of the Thermal Effects of MgO and ZnO Nanoparticles in a Pressurized Water Reactor Coolant with Computational Fluid Dynamics Model
Uzun, Sinem
When nanofluids are used as reactor coolants, they provide more effective heat transfer with their increase in thermal conduction properties. This plays an important role in energy production by increasing the efficiency of nuclear reactors. The present study delves into the thermal-hydraulic ramifications of utilizing nanofluids as coolants in the VVER-1000 nuclear reactor. Specifically, the thermal-hydraulic characteristics, encompassing parameters such as coolant temperature and departure from nucleate boiling ratio, were scrutinized in light of the incorporation of magnesium oxide (MgO) and zinc oxide nanoparticles. While performing these analyses, not only uranium but also thorium was used in the core as reactor fuel. Considering the emergence of thorium as a potential fuel material in nuclear technology, its inclusion in the fuel composition contributed to the originality of the research. With the addition of 0.2% MgO nanoparticles to a VVER nuclear reactor using 5% thorium dioxide (ThO2) fuel, the coolant temperature as a result of the channel flow was determined as 617.4 K (while 613.7 K for the light water). When employing thorium fuel (with an equivalent nanoparticle concentration), the maximum temperature exhibited an approximate increase of 3 deg compared to uranium fuel. With the addition of 0.2% MgO nanoparticles, the enthalpy value at the end of the channel was 1303.6 kJ/kg when using 5% ThO2 fuel, while the enthalpy value was determined as 1295 kJ/kg in 3.7% enriched UO2 fuel. As one of the most important results of the analysis, it was observed that the temperature value of the coolant increased when nanoparticles were used.
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ArticleYalnız künye2025/r/ebyu/11600
Electrochemical performance of Fe2Al1-xB2 MBene as a novel electrode material for supercapacitor applications
Tuzluca Yesilbag, Fatma Nur; Yesilbag, Yasar Ozkan; Huseyin, Ahmad; Salih, Ahmed Jalal Salih; Ertugrul, Mehmet
The growing global demand for efficient and sustainable energy storage systems has intensified the need for advanced electrode materials with superior performance and stability. This study focuses on the synthesis and characterization of Fe2AlB2 MAB phase and Fe2Al1-xB2 MBene, highlighting their potential for energy storage applications. The Fe2AlB2 MAB phase was synthesized using FeB and Al powders via high-temperature sintering (1200 °C for 2 h), followed by selective etching of aluminum layers with a 2 M HCl solution to produce Fe2Al1-xB2 MBene. Electrochemical measurements demonstrated that Fe2Al1-xB2 MBene exhibits excellent pseudocapacitive behavior, achieving a specific capacitance of 276 F g−1 at 0.5 A g−1 in a three-electrode system. An asymmetric supercapacitor (ASC) configuration achieved an energy density of 20.6 Wh kg−1 at a power density of 306.4 W kg−1, with 96 % capacitance retention after 10,000 cycles. This research represents one of the pioneering studies on Fe2Al1-xB2 MBene, emphasizing its potential as a high-performance electrode material for next-generation energy storage devices. The findings provide valuable insights into the design and application of 2D MBenes for energy-related technologies.
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ArticleYalnız künye2025/r/ebyu/11598
Explaining building energy efficiency prediction through architectural and engineering solutions considering environmental impacts using a hybrid model
Aslay, Semi Emrah
The aim of this study is to investigate building energy efficiency by integrating hybrid modelling approaches and interpretable models into architectural design processes and engineering solutions while considering environmental impacts. At the same time, it is aimed to achieve the most efficient building design possible. Separate analyses were carried out using a total of 6,913 data from Rutland (185) and Salford (6718) cities. The data were grouped into carbon emission information, architectural information, lighting information, personal heating information, and main heating system information to form a dataset. Light Gradient Boosting Machine (LightGBM) was preferred as the base model and Particle Swarm Optimisation (PSO) method was applied for hyperparameter optimisation. The hybrid model created in this way is called PSO-LightGBM. The optimization process was carried out using software in both R Studio and Python environments, utilizing seven different hyperparameters. Apart from the hybrid model used as a method, 2 different SHAP analyses, neural network based, and tree based, were performed to clearly explain the parameter relationships. The PSO-LightGBM hybrid model provided more successful predictions compared to the basic LightGBM model. While R2 values improved between 0.82 and 0.90 in the Rutland dataset, this value increased from 0.8687 to 0.8901 for test data and from 0.8538 to 0.9091 for training data in the Salford dataset. R2 values show an improvement of 7% in the Rutland dataset and maximum 6% in the Salford dataset. When the reduction in error rates is evaluated, it is found that the greatest improvement is in the Mean Squared Error (MSE) metric. MSE decreased by 17% in the Rutland dataset and by 4% in the Salford dataset. According to the SHAP Analysis results, CO2 emissions have the largest impact on energy consumption, while primary fuel types, number heated rooms and individual heating systems are other important parameters. While the tree-based SHAP model is more sensitive to physical parameters, the neural network model is more sensitive to indirect relationships. In both analyses, the communal heating system type has the lowest impact. In order to improve building energy efficiency, high efficiency individual boiler systems should be preferred, architectural approaches that optimise the number of heated rooms and smart heating solutions should be used, and central heating systems should be modernised. The results highlight the effectiveness of hybrid modelling approaches with SHAP analyses based on different baselines to ensure the integration of environmental impacts, architectural design processes and engineering solutions in terms of building energy efficiency. Furthermore, the findings contribute to the importance of interdisciplinary work in buildings to improve energy efficiency. Future studies can focus on the development of building energy performance prediction models that can be explained by integrating various learning algorithms and different optimisation techniques, using regions with high cooling demand, large datasets and different building types.
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ArticleYalnız künye2025/r/ebyu/11567
Building energy prediction model with AI-based PSO-ANN approach integrating architectural and HVAC processes
Aslay, Semi Emrah
Nowadays, due to the increasing energy demand, the importance of research on energy consumption estimation in buildings is increasing. This study aims to estimate and interpret energy consumption in buildings by integrating the processes of architecture and heating-ventilation-air conditioning (HVAC) components with an approach that combines environmental impact. For this purpose, the data were obtained from residential buildings in Nottingham and City of London, and the hybrid artificial neural network algorithm and Shapley Additive Explanations (SHAP) analyses were used as methods. To improve the performance of the Artificial Neural Network (ANN) model, a hybrid method was created with Particle Swarm Optimisation (PSO) (PSO-ANN). In order to ensure the interpretability of the model, both tree-based and neural network-based SHAP method were used. The outputs of this AI-supported method were compared and interpreted. The hybrid model developed in this study achieved an R-squared value of 0.99 in the test data sets in both data groups, which is a significant improvement compared to standard ANN models (0.95–0.97). In addition, when the training data is also included, the overall improvement rate is calculated as 3–5 %. According to the results of the analyses, CO₂ emission rate and total area are the factors that affect the energy consumption the most. In addition, the positive effects of heating control systems and lighting factors on energy efficiency are evaluated, and their importance is emphasized. These results provide an effective prediction model that combines building energy consumption and environmental performance and integrates the processes of architecture and HVAC components.
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ArticleYalnız künye2025/r/ebyu/11533
Deep learning and adaptive boosting for hydroelectric power prediction using hydro-meteorological data: Insights and feature importance analysis
Karakoyun, Yakup; Katipoğlu, Okan Mert; Dogan, Ahmet
This study explores the use of modern artificial intelligence (AI) models such as Adaptive Boosting (AdaBoost), Autoencoder Based Regression Model (Autoencoder), Deep Neural Network (DNN), Echo State Network (ESN), Light Gradient Boosting Machine (LGBM) Residual Neural Network (ResNet) and feature importance techniques to predict energy production. Daily rainfall, streamflow, temperature and energy production data between 2016 and 2019 were used in the study. According to the feature importance analysis performed using the LGBM model, streamflow, temperature, and precipitation were identified as the most critical parameters influencing energy production. This structured AI-driven approach provided robust model evaluation and reliable performance measurements. As revealed by the analysis, the LGBM model showed the most accurate result with the values of root mean square error (RMSE: 98.27), mean absolute error (MAE: 73.93), Akaike information criterion (AIC: 17,100), Nash–Sutcliffe efficiency coefficient (NSE: 0.69), Kling–Gupta efficiency (KGE: 0.77), coefficient of determination (R2: 0.69), mean bias error (MBE: −5.23), bias factor (BF: 1.02), and percent bias (PBIAS: 1.51), while the DNN model came in with the second-best results. These findings emphasize both the effectiveness of deep learning and ensemble AI models and their practical application in improving hydroelectric power generation forecasting. Furthermore, the study underscores the importance of accurately monitoring and managing streamflow for the optimization of hydroelectric systems.
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ArticleAçık Erişim2025/r/ebyu/11518
Efficient Soft-Switching Snubber Cell Design for PWM DC-DC Boost Converters: Enhanced Load-Independent Performance
Sahin, Yakup; Ting, Naim Suleyman
Soft-switching (SS) boost converters are extensively utilized in applications such as renewable energy systems, electric vehicles, and high-efficiency power supplies, as they offer reduced switching losses and enhanced overall efficiency. Zero-voltage transition (ZVT) snubber cells that used SS operation perform poorly in zero-voltage switching (ZVS) turn-off at light load, although they perform well at heavy load. This study proposes a novel SS snubber cell for the PWM-DC boost converter, ensuring excellent ZVS turn-off performance under all load conditions. The main switch is turned off with ZVS at heavy and light load, so the turn-off performance is independent of the load conditions. In addition, the main switch is switched on with ZVT, and the main diode is switched with SS. The main and auxiliary semiconductor components do not expose additional voltage. In addition, the semiconductor switches are switched on with zero-current switching (ZCS) and switched off with ZVS, whereas the auxiliary diode is switched with SS. The theoretical analysis of the converter is presented, and an experimental study is conducted to demonstrate the analysis. The proposed converter is operated with an output power of 500 W and a switching frequency of 100 kHz.
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Review ArticleAçık Erişim2025/r/ebyu/11452
Nitrogen-doped MXene for supercapacitor: A review
Salih, Ahmed Jalal Salih; Huseyin, Ahmad
Efforts to enhance the properties of MXene have been ongoing since its discovery in 2011. Various strategies have been explored to improve its performance for many applications. One such strategy is doping MXene with heteroatoms. Doping has been studied for several applications, including supercapacitors, with particular attention given to nitrogen doping. This review focuses on doping MXene with nitrogen for supercapacitor applications. It discusses the effects of doping on the chemical, physical, and structural properties of MXene, the doping mechanisms (lattice substitution, functional substitution, and surface adsorption), and the contributions of each mechanism to the enhancement of electrochemical performance. Additionally, the review discusses doping methods and their impact on the performance of MXene as supercapacitor electrodes. It presents results from experimental studies and discusses several of these findings. Finally, it provides recommendations to guide future research and optimize outcomes in this field.
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Review ArticleYalnız künye2025/r/ebyu/11414
Batteries and supercapacitors: An analytical perspective on electrode materials and performance challenges
Huseyin, Ahmad; Salih, Ahmed Jalal Salih
Energy storage devices, especially batteries and supercapacitors, are essential components in portable electronics and electric vehicles, and their role in supporting renewable energy systems is becoming increasingly critical. This review investigates their principles, types, and performance challenges, with a particular focus on energy density, power density, charge/discharge rates, and cycle life. While lithium-ion batteries are widely used for their high energy density, they face significant challenges such as long charging times, high costs, and safety concerns. Consequently, alternative battery technologies, including lithium-sulfur, lithium-air, sodium-ion, and zinc-based systems, are under active investigation. Supercapacitors, known for their rapid charge/discharge cycles and high power density, are limited by their low energy density. A key area of ongoing research is the optimization of electrode materials, such as carbon-based compounds, metal oxides, and conductive polymers, to enhance the performance of both batteries and supercapacitors. This work discusses the mechanisms of energy storage, electrode degradation, and electrolyte stability, while offering insights into future developments. It underscores the importance of distinguishing between the performance characteristics of batteries and supercapacitors to avoid misconceptions, as each technology operates on distinct principles that affect their efficiency and applications.
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ArticleYalnız künye2025/r/ebyu/11292
Ti2NbC2Tx MXene Nanosheets as an Ordered Double Transition Metal Electrode for High-Performance Supercapacitors
Tuzluca Yesilbag, Fatma Nur; Yesilbag, Yasar Ozkan; Huseyin, Ahmad; Salih, Ahmed Jalal Salih; Ertugrul, Mehmet
The increasing demand for advanced materials in energy storage underscores the importance of chemical diversity in nanomaterials. Ordered double transition metal (DTM) MXenes have emerged as promising atomically layered 2D materials. This study investigates the flexible Ti2NbC2Tx MXene, synthesized from the ordered Ti2NbAlC2 MAX phase, as a supercapacitor electrode material. Electrochemical analyses revealed specific capacitances of 322 and 642 F g-1 at a current density of 0.5 A g-1 in Na2SO4 (Na) and H2SO4 (H) electrolytes, respectively. Ti2NbC2Tx MXene exhibited exceptional cycling stability, retaining 95% capacitance in Na2SO4 and 100% in H2SO4 after 10,000 charge/discharge cycles. Furthermore, an asymmetric supercapacitor (ASC) was fabricated using Ti2NbC2Tx MXene as the positive electrode and overcapacitive activated carbon as the negative electrode with PVA-Na and PVA-H gel electrolytes. The ASC achieved energy densities of 31.1 and 34.0 W h kg-1 for PVA-Na and PVA-H electrolytes, respectively. These results highlight the potential of Ti2NbC2Tx MXene, with its unique ordered structure and double transition metal composition, for foundational research and applications in advanced energy storage technologies.
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ArticleYalnız künye2025/r/ebyu/11258
Enhanced soft-switched T-type neutral-point clamped (T-NPC) inverter with reduced component number
Ozgenel, Mehmet Cihat; Ting, Naim Suleyman; Sahin, Yakup
This paper presents an enhanced soft-switched T-type neutral-point clamped inverter featuring a compact active snubber cell that delivers zero-voltage transition turn-on and zero-voltage switching (ZVS) turn-off for the main switches, while auxiliary switches operate with zero-current switching turn-on and ZVS turn-off. Unlike prior designs, four auxiliary-path diodes are eliminated, reducing component count, conduction path length, and reverse-recovery losses, which in turn lowers cost, eases thermal management, and boosts power density. The proposed topology maintains full soft switching (SS) for all active devices without introducing additional voltage or current stress. The theoretical analysis of the inverter is clarified, and the operating modes for steady-state analysis are presented in detail. Experimental validation on a 400 V, 1 kW, and 100 kHz prototype demonstrates consistent SS across load conditions and a peak efficiency of 97.2%. The combination of higher efficiency, structural simplicity, and cost-effectiveness makes the proposed inverter a strong candidate for high-performance, compact T-type applications in renewable energy, and electric drive systems.
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ArticleAçık Erişim2025/r/ebyu/11110
Time-varying dynamics of energy and sustainability uncertainty
Kuziboev, Bekhzod; Çatık, A.Nazif; Pícha, Kamil; Makhmudov, Samariddin; Matyakubova, Aziza; Balli, Esra
This article examines the link between energy-related uncertainty and sustainability uncertainty by utilizing monthly data from November 2002 to October 2022. To this aim, wavelet coherence and time-varying parameter vector autoregression (TVP-VAR) methodologies are utilized. Wavelet coherence results uncover statistically significant long-term correlation between energy and sustainability uncertainties, particularly during periods of global economic crises. The time-varying responses reveal that the impact of energy-related uncertainty shocks is positive over the analysis period. The impacts of energy-related uncertainty are found to be more pronounced during the turbulent periods, such as the 2008 global financial crisis and the COVID-19 pandemic. The time-varying impact of global economic activity on the sustainability uncertainty does not follow a stable trajectory, and it is not statistically significant. The time-varying impact of financial stress on the sustainability uncertainty is not stable, including both positive and negative effects over the analysis period. The results generally reveal the complex interconnections between energy markets, economic conditions, and sustainability issues. This evidence highlights the importance of policymakers taking these connections into account when formulating strategies for energy security and sustainable development, particularly during periods of global economic uncertainty.
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ArticleYalnız künye2025/r/ebyu/11090
Solvothermal synthesis of ZnV2O6/g-C3N4 composites for high-performance supercapacitors
Yaldır, Onur; Karabiberoğlu, Şükriye; Koçak, Çağrı Ceylan; Yavuz, Emre; Özdokur, Kemal Volkan; Dursun, Zekerya
Composite materials formed by combining mixed metal oxides and graphitic carbon nitride have gained significant attention in recent years for energy applications. Here, a novel material was obtained by combining ZnV2O6 mixed metal oxide structure synthesized by the solvothermal method with g-C3N4 prepared by pyrolysis. SEM, XPS, XRD, FTIR, and TGA techniques were employed for comprehensive material characterization. The synthesized ZnV2O6/g-C3N4 was then used in supercapacitor studies. The resulting composite material demonstrated a specific capacity of 438 F g−1 at 1.5 A g−1 in 6.0 M KOH solution. After 2500 cycles, it retains 96 % of its capacitance, demonstrating excellent cyclic stability. Furthermore, a symmetric supercapacitor device based on ZnV₂O₆/g-C₃N₄ electrodes was assembled and tested, achieving high capacitance retention over extended charge–discharge cycles. The synergistic effect of g-C3N4, with its large surface area and chemical stability, and ZnV2O6, with its fast electron transfer ability, has resulted in the formation of the composite with enhanced performance.
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ArticleAçık Erişim2025/r/ebyu/10983
Integrated Emission and Cost Analysis of Battery-Electric Vehicles up to 2035
Demirci, Oğuz Kürşat
This study quantifies when battery-electric vehicles (BEVs) reach total cost of ownership (TCO) parity with their internal-com-bustion counterparts and characterises the cradle-to-grave greenhouse-gas (GHG) intensity trajectory to 2035. Our contribution is a transparent, Python-based framework that integrates battery-cost learning, ownership economics and life-cycle impacts within a harmonised scenario set, and links them to policy timing, ISO 15118-20-ready bidirectional charging and power-system carbon intensity. Drawing on a systematic synthesis of 221 peer-reviewed sources (2013–2025), the model runs annually for a representa-tive C-segment BEV across three scenarios (Reference, Fast-Progress, Slow-Progress; 2024–2035). The results indicate that, under the median battery-pack price learning trajectory, BEV TCO falls below the ICE benchmark around 2029 (2028–2032 across sce-narios), while life-cycle GHG intensity declines from approximately 73 to 34 g CO2-eq km-1 by 2035, spanning 29–42 g km-1 depending on grid decarbonisation. Global sensitivity analysis identifies battery price as the principal driver of TCO outcomes and grid carbon intensity as the principal driver of emissions outcomes. Results are reported for three regional aggregates (OECD average, EU-27 and China), and the policy discussion highlights contrasts for the United States to contextualise cross-market dif-ferences. Policy alignment on three fronts—parity-linked purchase-incentive phase-outs, rapid deployment of ISO 15118-20-ready bidirectional charging, and stronger recycled-content targets—shortens time to cost competitiveness and amplifies the climate ben-efits of large-scale electrification.
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