Yazarlar
- Akkurt, Nevzat(24)
- Kahraman, Gökhan(17)
- Sabanci, Serdal(11)
- Tuğan, Volkan(9)
- Işık, Erdem(8)
- Xu, Qian(8)
- Xiong, Yaxuan(7)
- Yucesan, Melih(7)
- Goksu, Ali(6)
- Demir, Yakup(5)
- Gul, Muhammet(5)
- Aghakhani, S.(4)
- Cevik, Mutlu(4)
- Icier, Filiz(4)
- Liu, Lin(4)
- Mahmoud, Mustafa Z.(4)
- Taşgın, Yahya(4)
- Yang, Gang(4)
- Yardımcı, Uğurcan(4)
- Younis, Obai(4)
- Yüzüak, E.(4)
- Yüzüak, G. Durak(4)
- Yüzüak, Gizem Durak(4)
- Çevik, Mutlu(4)
- Özdemir, Osman(4)
- Chen, Xingli(3)
- Ding, Yulong(3)
- Du, Yanping(3)
- Erdem, Necla Seval(3)
- Gunay, Mihriban(3)
- Göçmen, Elifcan(3)
- Hussein, Ahmed Kadhim(3)
- Karakaya, Hakan(3)
- Konurhan, Zekeriya(3)
- Qiang, Yujie(3)
- Sabancı, Serdal(3)
- Wang, Zhaoxiao(3)
- Yilmaz, Mehmet(3)
- Yüzüak, Ercüment(3)
- Zhang, Hui(3)
Yayınlar
- MakaleYalnız künye2026Scopus SJRQ1Mechanical and durability properties of sustainable alkali-activated mortars with ceramic insulator waste and andesite powder as partial substitutes for GBFS
Cemalgil, Selim; Yön, Merve Şahin; Dener, Murat; Karataş, Mehmet
This study explores the use of andesite powder (AP) and ceramic waste powder (CWP), derived from discarded electrical insulators, as supplementary precursors to ground granulated blast furnace slag (GBFS) in alkali-activated self-compacting mortars. The originality of the work lies in the combined utilization of these regionally sourced aluminosilicate wastes in binary and ternary binder systems, aiming to reduce GBFS dependency while ensuring adequate mechanical and durability performance. AP and CWP were used to replace GBFS at up to 50%, and the mixtures were evaluated for flowability, mechanical strength, density, porosity, water absorption, and capillary sorptivity. Durability was assessed through freeze–thaw cycling and high temperature exposure, and microstructural characteristics were examined using scanning electron microscope analysis. Results showed that while partial substitution with AP or CWP reduced compressive strength compared to the GBFS control, the incorporation of CWP in ternary systems partially compensated for the strength losses associated with AP. High temperature resistance improved markedly with increased CWP content; at 900°C, the 50% CWP mixture retained 44% of its original compressive strength, in contrast to 8% for the control. Although all mixtures containing waste exhibited reduced freeze–thaw resistance, mortars containing CWP exhibited superior performance compared to those with only AP. These findings highlight the potential of CWP, particularly in ternary systems, for developing sustainable alkali-activated mortars.
AtıfScopus16WoS14OpenAlex12
İncele - MakaleAçık Erişim2026Scopus SJRQ1Numerical analysis of PCM integrated in solar dryers for thermal efficiency
Bakır Gür, Eda; Işık, Erdem; Uçar, Aynur
Solar dryers using phase change materials buffer heat, yet the combined influence of airflow regime and PCM placement on melting remains underexplored. A controlled like-for-like study fixed geometry and PCM properties while varying placement and operating conditions. A 3D transient CFD model simulated a forced-convection dryer with RT28HC over Re = 3000–9000 and inlet temperatures Ti = 50–60 °C. Raising either Re or Ti shortened melt time, and three-wall coverage melted faster and more uniformly than a rear-wall-only layout. For three walls, melt time dropped from 13 h (50 °C, Re = 3000) to 7 h (60 °C, Re = 9000) (−46 %) for the rear wall it fell from 19 h to 11 h (−42 %). A 10 °C increase in Ti reduced overall melt time by 4 h across Re. Practically, three wall PCM with Re ≥ 6000 at Ti = 60 °C achieved reliably 7–9 h melting, enabling late afternoon heat release without auxiliary heating.
AtıfScopus17WoS16OpenAlex12İncele - MakaleAçık Erişim2026Scopus SJRQ3An Artificial Neural Network Modeling of Solar Drying of Mint: Energy, Exergy, and Drying Kinetics
Gülçimen, Fevzi; Karakaya, Hakan; Durmuş, Aydın
Abstract: Solar drying is an environmentally friendly method for preserving agricultural products; however, limited studies have jointly examined energy–exergy performance and data-driven prediction methods under varying airflow conditions, which restricts performance optimization. This study aims to investigate the effects of inlet airflow rate on energy utilization ratio, energy generation, exergy loss, exergy efficiency, and drying kinetics of mint leaves, and to evaluate the predictive capability of artificial neural network modeling. Thin-layer drying experiments were conducted in a forced convective solar dryer equipped with a newly designed solar air collector at different air mass flow rates. Energy and exergy analyses were conducted using experimental thermodynamic data, and energy utilization and exergy loss were modeled with a feed-forward back-propagation artificial neural network. The energy utilization ratio ranged from 7.45 to 87.1% and increased with decreasing airflow rate. The average exergy losses for air mass flow rates of 0.012, 0.026, and 0.033 kg s–1 were 16.2, 8.2, and 6.88 W, respectively. Both experimental and artificial neural network results showed that increasing airflow rate reduced energy utilization ratio and exergy loss. The artificial neural network predictions exhibited very close agreement with experimental data. The results show that artificial neural networks can accurately predict energy utilization ratio and exergy loss in a forced convective solar dryer. Airflow rate is a key parameter for thermodynamic performance, and the integrated experimental–ANN approach offers a robust tool for optimizing and designing solar drying systems.
AtıfOpenAlex1İncele - MakaleYalnız künye2026Scopus SJRQ1Computational fluid dynamics analysis of battery pack with cooling channel integrated with innovative thermoelectric cooling stations
Yardımcı, Uğurcan; Tuğan, Volkan
In this study, a novel liquid cooled battery thermal management system integrated with a thermoelectric assisted cooling channel has been designed. To prevent battery cells from operating at high temperatures and to ensure a uniform temperature distribution among the cells, multiple thermoelectric stations were placed at various positions along the cooling channel. The performance of four different models created with various temperature combinations, as well as a conventional model without thermoelectrics, was investigated through Computational Fluid Dynamics simulations. In the analyses, five different thermoelectric temperatures (293.15–298.15 K), two different mass flow rates (0.0013 and 0.0018 kg/s), and two different initial temperatures (298.15 and 303.15 K) were examined. The results demonstrated a significant improvement in the performance of the battery thermal management system with the use of the thermoelectric assisted cooling channel. It was determined that lowering the initial temperature from 303.15 K to 298.15 K and increasing the mass flow rate from 0.0013 kg/s to 0.0018 kg/s resulted in better cooling performance and more uniform distribution for the thermoelectric assisted system. Under the conditions of a 0.0013 kg/s mass flow rate and an initial temperature of 303.15 K, the highest reduction in maximum battery temperature, compared to the non-thermoelectric design, was achieved in Model B with 9.207 K. Under the same conditions, the most significant reduction in maximum temperature difference was observed in Model D with 4.758 K. Furthermore, the Root Mean Square Spread analysis results revealed that Model B provided the best performance in terms of temperature distribution.
AtıfScopus7WoS7OpenAlex10İncele - MakaleAçık Erişim2026Scopus SJRQ2Production and Thermal–Structural Characterization of Nano-Oxide-Doped Paraffin-Based Phase Change Composite Materials for Thermal Storage Applications
Yücel, Halit Lutfi; Özdemir, Osman; Kahraman, Gökhan
Paraffin-based composite phase change materials (PCMs) have been synthesized for thermal energy storage applications to enhance thermal conductivity and stability while maintaining latent heat storage capacity. In this study, RT42 paraffin was modified with inorganic nano-oxides (Al2O3, CuO, SiO2, and ZnO) in the presence of sodium dodecyl sulfate (SDS) as a surfactant. The incorporation of SDS improved nanoparticle dispersion and reduced agglomeration, resulting in enhanced phase-change behavior and improved structural homogeneity. Differential scanning calorimetry (DSC) analysis revealed slight variations in melting and crystallization temperatures, while the ZnO-doped composite retained up to 92% of the latent heat storage capacity of pure RT42. Among all the investigated composites, the Al2O3-doped sample exhibited the highest thermal conductivity and specific heat capacity. Thermogravimetric analysis (TGA) indicated an increase of approximately 15–20°C in the decomposition temperature, demonstrating enhanced thermal stability. X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses confirmed the preservation of the crystalline structure and improved microstructural uniformity. The developed SDS-assisted nano-oxide/RT42 composites exhibit significant potential for passive thermal regulation in renewable energy and building applications.
AtıfScopus1WoS1OpenAlex1İncele - MakaleYalnız künye2026Scopus SJRQ2Experimental ınvestigation of hybrid passive cooling strategies for photovoltaic modules using nano-enhanced PCM and graphene-coated finned structures under hot climate conditions
Özdemir, Osman; Yücel, Halit Lutfi; Kahraman, Gökhan
This study experimentally investigates the use of several passive cooling techniques to enhance the electrical performance of photovoltaic (PV) modules under high ambient summer temperatures in Elazığ, Turkey. Throughout the trial period of July, August, and September, a system comprising four photovoltaic panels, one designated as a reference, was developed. The first passive cooling arrangement utilized a paraffin-based phase change material (PCM) RT42HC. In the second configuration, a nano-enhanced PCM (NePCM) composite was employed, prepared by dispersing 1 mass% of Al2O3 nanoparticles into the paraffin matrix and stabilizing them with 3 mass% of sodium dodecyl sulfate (SDS) to ensure homogeneous distribution. The third, hybrid configuration integrated 14 graphene-coated parabolic pin-tipped fins mounted externally onto the aluminum enclosure housing the NePCM composite. Experimental results demonstrated that the implemented passive cooling techniques markedly decreased the panel surface temperature, thereby enhancing electrical power output and photovoltaic efficiency. The hybrid graphene-coated fin-NePCM system demonstrated superior performance, achieving a maximum surface temperature reduction of 12.65 °C, a sustained electrical efficiency increase of 6–13%, and an average daily electrical energy gain of 26.23 Wh day−1 compared to the reference module. These findings demonstrate that the integrated hybrid design is an effective and reliable passive cooling method for sustaining photovoltaic system performance under hot climate conditions.
- MakaleAçık Erişim2025Investigation of the Benefits of the Floating Solar Power Plant to be Established on Keban Dam Lake using Penman, Linacre and Artificial Neural Networks Methods
Esen, Hikmet; Kurt, Savaş; Toka, UnalT Unal
In this study, it will be calculated how much water evaporation will be prevented if a Floating Solar Power Plant (FSPP) is installed on a certain part of the Keban Dam lake in Elazığ (38.41˚N, 39.14˚E), Türkiye by using the Penman and Linacre methods and the Artificial Neural Networks (ANN) method, which are widely used in evaporation calculation. Thus, it will be calculated how much energy can be produced with this saved water. Keban Hydroelectric Power Plant (HPP), examined in this study, is Türkiye's 3rd largest hydroelectric power plant with an installed power of 1.330 MWe. It is the fourth largest lake in Türkiye and the second largest dam lake after the Atatürk Dam. Keban Dam meets the electrical energy needs of 1.750.733 people in their daily lives with an average electricity production of 5.794.927,279 kWh. It has been calculated that thanks to a floating photovoltaic power plant that will cover 10% of the dam lake, a total of 31.305.282 m3 of water in normal water code will be prevented from evaporating annually, and thanks to this water, energy benefit will be provided with the power plant with an installed power of 6.624,84 MWe. In addition, it has been analyzed that 11.297.018 kWh of electricity can be produced from the dam turbines with the water prevented from evaporating thanks to FSPP. Approximately 72.39 MWe energy is needed for the Ağın, Pertek, Serince, Palu-Kovancılar, Uluova, Kuzova irrigation projects around the Keban Dam lake. It has been determined that the amount of water and energy needed for irrigation of these plains can be obtained thanks to FSPP.
- MakaleAçık Erişim2025Determination of Suitable Drying Model and Energy Efficiency of Mixed Culture Microalgal Biomass by Infrared Drying
Yoğurtçu, Hakan; Kalender, Mehmet
In this study, a modeling approach using infrared (IR) drying data of mixed-culture algae, an energy efficiency analysis of the drying process, and some surface proper-ties of the dried product were presented. New model equations derived from com-monly known drying models were applied to experimental data obtained from drying microalgal biomass at various temperatures ranging from 5 to 105 °C. Among these, the DM13 equation, based on the Newton model, best represented the drying behav-ior. The specific moisture extraction rate (SMER) and moisture extraction rate (MER) increased with higher drying temperatures, while, as expected, the specific energy consumption (SEC) decreased. According to the energy efficiency analysis, the IR drying method can be considered suitable for drying microalgal biomass. FT-IR re-sults indicated characteristic green algae peaks attributed to components such as carbohydrates, proteins, and cellulose–fatty acids. Peaks at 2900 cm⁻¹ and 3386 cm⁻¹ decreased with increasing drying temperature and disappeared at 105 °C. SEM imag-es showed that microalgal cells experienced shrinkage at 60 °C. Furthermore, while dried microalgal biomass exhibited a porous structure at 50 °C and 60 °C, pores were almost absent at 70 °C and 105 °C.
- MakaleAçık Erişim2025Elazığ İli Örneğine Ait On-Grid Çatı Üstü Güneş Enerji Santralinin Yıllık Gerçek Üretim Verilerinin PV*SOL Simülasyon Değerleri ile Karşılaştırılması
Celik, Ertugrul; Özdemir, Osman
Geçmişten bugüne kadar insanoğlunun temel gereksinimlerinin karşılanması için enerjiye ihtiyaç duyulmaktadır. Dünyada nüfusun hızlı bir şekilde yükselmesi, teknolojik faaliyetlerin gelişimiyle birlikte enerji tüketimi gün geçtikçe artmaktadır. Günümüzde artan enerji talebini karşılamak için fosil yakıtlar ve yenilenebilir enerji kaynakları kullanılmaktadır. Yenilenebilir enerji kaynakları, doğal süreçler aracılığıyla sürekli olarak yenilenen ve fosil yakıtlarla karşılaştırıldığında düşük emisyon değerlerine sahip olan çevre dostu enerji üretim kaynaklarıdır. Güneş enerjisi sistemlerindeki teknolojik ilerlemeler, maliyetlerin düşmesi ve verimliliğin artması, güneş enerjisini yenilenebilir enerji kaynakları arasında güçlü bir alternatif haline getirmektedir. Özellikle arazi ve çatılara kurulan Güneş Enerji Santrallerinin (GES) sayısı gün geçtikçe artmaktadır. Bu çalışmada Elazığ ili sınırları içinde sanayi bölgesinde bir işletmenin çatısına kurulmuş şebekeye bağlı çatı (on-grid) üstü GES sistemi ele alınmıştır. Çatı üstü GES toplam 165 adet, 545 Watt gücünde monokristal panellerden oluşmakta olup toplam gücü 89,9 kWp’tir. Sistem performansını artırmak amacıyla seçilen alan için en iyi yönelimi ve eğim açısını bulmak amacıyla PV*SOL yazılımı kullanıldı. Bu çalışmada mevcut GES sisteminin bir yıllık enerji üretim verileri aylara göre incelenerek, PV*SOL simülasyonunda elde edilen benzetim sonuçları ile karşılaştırılarak PV*SOL yazılımının doğruluk oranı değerlendirilmiştir. Çalışma sonucunda PV*SOL simülasyon programından elde edilen veriler ile çatı üstü GES gerçek verileri arasında %0,03 fark olduğu tespit edilmiştir. Bu sonuçlar göz önüne alındığında, uygulaması yapılan enerji sisteminin teknik ve ekonomik olarak uygun olduğu söylenebilir.
AtıfOpenAlex1
İncele - MakaleAçık Erişim2025Predicting daily energy consumption in ev charging stations using tree-based models
Ertarğın, Merve
Electric vehicles (EVs) have emerged as a cornerstone in the transition toward sustainable transportation, offering a cleaner alternative to conventional fossil fuel-based mobility. Their integration into modern transportation systems not only supports global decarbonization efforts but also requires robust energy management solutions to address the growing demands on charging infrastructure. Ensuring efficient energy consumption forecasting is vital for optimizing EV charging station operations and maintaining grid stability. This study aims to predict the daily energy consumption of an EV charging station using a public dataset. Key features such as charging duration, vehicle count, mean and median connection time were utilized for the prediction. Both the original dataset and its z-score-cleaned version were employed to evaluate the models' performance under different data conditions. Decision Tree (DT), Random Forest (RF), Extreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM) models were implemented, with hyperparameter optimization conducted via GridSearchCV. The results revealed that all four models achieved high accuracy in predicting daily energy consumption across both datasets, with R2 values exceeding 0.97. Specifically, for the z-score-cleaned dataset, LightGBM demonstrated the best performance with the lowest RMSE (37.35 kWh) and MAE (28.93 kWh), as well as the highest R2 value (0.9727) followed by XGBoost, RF and DT.
AtıfOpenAlex1İncele - MakaleAçık Erişim2025Scopus SJRQ1Rejuvenation of Recycled Asphalt Binders with Bio-Oils from Waste Biomass Pyrolysis
Yalcin, Beyza Furtana; Yilmaz, Mehmet; Yalçin, Erkut; Altundogan, Hamdi Soner
This study evaluates the effects of using bio-oil obtained from waste biomass on the physical properties, rheology, fatigue, and rutting of recycled asphalt binder. In addition, the aim of this study is to provide benefits to the environment and the economy by reusing waste materials. The bio-oils produced were produced by the pyrolysis method. B70/100 pure bitumen was chosen as the reference binder for the rejuvenation of the selected RAP binder. To ensure its properties, five different rejuvenators (two commercial + three bio-based rejuvenators) were added to the aged bitumen obtained from recycled asphalt pavement (RAP) at different rates. The produced bio-oils were compared with commercial products. The first goal of the study is to produce rejuvenators from waste materials, and the second is to achieve similar or better results with commercial rejuvenators by producing rejuvenators from waste materials. When the test results are examined, it can be seen that the aged binder was rejuvenated to the desired hardness by adding rejuvenator to it. It is seen that the penetration value of the aged binder increased by the addition of rejuvenator, whereas the softening point and viscosity values decreased.
AtıfWoS1OpenAlex1İncele - BildiriAçık Erişim2025Deep Learning-Based Approaches for Short-Term Residential Electricity Consumption Prediction: A Comparative Study of LSTM, CNN-LSTM, and CNN-GRU Models
Gunay, Mihriban; Yildirim, Ozal; Demir, Yakup; Benedicenti, L.; Liu, Z.
The rapid increase in the world population has increased electricity consumption and demand for electricity. In order for electricity distribution companies to determine electricity demand, household electricity consumption must be predicted. In this study, an open access dataset was used to predict individual household electricity consumption. For this purpose, deep learning-based LSTM, CNN-LSTM and CNN-GRU models were developed and a comparative analysis was performed. The performance of the models was evaluated using four evaluation metrics commonly used in prediction model performance evaluation. According to the results obtained, it was seen that the models used in the study were successful in predicting short-term electricity consumption. In particular, the CNNLSTM model was found to have a lower error rate compared to the other two models.
- MakaleAçık Erişim2025Scopus SJRQ2Forecasting daily natural gas consumption with regression, time series and machine learning based methods
Yucesan, Melih; Pekel, Engin; Celik, Erkan; Gul, Muhammet; Serin, Faruk
An effective short-term natural gas forecasting method contributes to social contributions and allows industrial chain elements to function effectively and minimize economic losses. We dealt with a comparative framework on the applicability of different methods in daily natural gas service (NGS) consumption forecasting. In this context, time series, machine learning, evolutionary and population-based approaches, and their hybrid versions are applied to the NGS data. Hybridized approaches are tested in the scope of NGS consumption forecasting for the first time in the literature in this study. The case of Turkey is handled, and its NGS data is used to demonstrate the comparative framework’s applicability. The comparative study is assessed in the lights of common forecasting accuracy measures of mean absolute percentage error (MAPE), R-squared (R2), and mean squared error (MSE). According to each method’s results, the seasonal autoregressive integrated moving average with exogenous regressors (SARIMAX) and artificial neural network (ANN) hybrid model provides the most dominant performance with respect to MAPE. The lowest error was obtained with a MAPE value of 0.357 in this hybrid model constructed under seven neurons in its ANN structure. This model is followed by another hybrid model, autoregressive integrated moving average (ARIMA)-ANN, with a MAPE value of 0.5 under nine neurons in terms of accuracy performance. The worst performance value belongs to the Genetic algorithm-ANN hybrid model with a MAPE value of approximately 26%.
AtıfScopus16WoS19OpenAlex22İncele - MakaleYayıncıda açık erişim2025Scopus SJRQ1Experimental analysis of a double-slope solar still integrated with parabolic trough solar collector using nanofluid
Tuğan, Volkan; İnallı, Mustafa; Işık, Erdem
The use of solar energy in the treatment of saline water offers a sustainable and low-cost solution to the increasing global fresh water demand. In this direction, solar still systems separate water vapor from saline water by directly using solar radiation and then condense it to obtain pure water. However, their fresh water productivity is relatively low. Therefore, in this study, the fresh water productivity and thermal efficiency of the double slope solar distillation unit integrated with parabolic trough solar collector, which operates completely on solar energy, were investigated experimentally. In addition, the effect of water-based nanofluid containing multi-walled carbon nanotubes on the performance of the solar still was investigated. All the stills produced were compared in terms of fresh water productivity and thermal efficiency. According to the results obtained from the study, the highest daily productivity was found to be 1963.8 g/m2/day, 2008.5 g/m2/day, 2592.0 g/m2/day and 2937.6 g/m2/day for SSSS, DSSS, PTSC integrated DSSS and both NF and PTSC integrated DSSS, respectively. It was observed that the daily productivity of DSSS, DSSS with integrated PTSC, and DSSS with both PTSC and NF were 6.6 %, 42.2 %, and 49.6 % higher than SSSS, respectively. Additionally, it was observed that the thermal efficiency of DSSS using PTSC and NF was lower compared to SSSS due to its larger system area.
AtıfScopus13WoS8OpenAlex10İncele - MakaleAçık Erişim2025Scopus SJRQ1Thermophysical properties and Optimization of modified palm Oil-Amine reinforced biocomposites for lightweight and insulating applications
Şahal, Hakan; Aydoğmuş, Ercan; Arslanoğlu, Hasan
The aim of this study is to investigate various thermophysical properties of modified palm oil-amine (MPOA) reinforced biocomposites to optimize these materials to meet the requirements of lightness and insulation. The effects of MPOA addition to biocomposites on bulk density, surface hardness, thermal conductivity coefficient, and activation energy have been evaluated. In addition, the structural and physical properties of these biocomposites are aimed to determine their potential use as lightweight and thermal insulation materials. The results show that MPOA incorporation significantly affects the bulk density, Shore A hardness, thermal conductivity, and thermal stability of biocomposites. The addition of MPOA provides significant benefits for lightweight biomaterials by reducing bulk density. However, high MPOA content decreases the surface hardness of the biocomposite, and with zirconium silicate (ZrSiO4), this drawback is eliminated and the curing time is reduced. Increasing MPOA ratios also improve the insulation properties of biocomposites by reducing the thermal conductivity coefficient. Thermal decomposition experiment results show that higher MPOA content reduces thermal stability. Scanning electron microscopy (SEM) reveals that high levels of MPOA lead to increased surface porosity and irregularities, negatively affecting surface morphology. An optimal MPOA reinforcement level of 5 wt% provides a balance between desirable properties such as reduced density and improved thermal insulation while minimizing adverse morphological effects. Fourier-transform infrared spectroscopy (FTIR) confirms the presence of epoxy resin and the successful chemical modification of palm oil to create bioepoxy feedstock. MPOA reinforcement offers benefits such as reduced bulk density and improved thermal insulation while addressing challenges in surface morphology, mechanical properties, and thermal stability. The study concludes that biocomposites with 5 wt% MPOA provide optimum stability, making them suitable for applications requiring lightweight and thermally insulating materials without significantly compromising structural integrity. This research, the long-term performance of biocomposites, and future investigations into their potential applications will further expand their practical applicability.
AtıfScopus2WoS2OpenAlex2İncele - MakaleAçık Erişim2025Scopus SJRQ1High-Entropy Alloys and Oxides as Supercapacitor Electrodes: A Structural and Electrochemical Perspective for Energy Storage
Başgöz, Öyküm; Güngör, Ahmet; Güler, Ömer; Erdem, Emre
This study investigates the performance of high entropy alloys [Fe3Cr3Mn2NiV, HEA)] and high entropy oxides [(Fe3Cr3Mn2NiV)O4, HEO)] as electrode materials for supercapacitors. HEA is synthesized through mechanical alloying, followed by HEO forming via an oxidation process. XRD results demonstrate HEA comprises both amorphous and crystalline phases, whereas HEO has an entirely crystalline structure. SEM analyses showed HEA exhibits larger and irregular particles, whereas HEO displays a smaller and spherical morphology. EPR analyses revealed significant changes in defect structures and unpaired electron configurations during the transition from HEA to HEO. HEA is prone to diffusion-controlled processes due to their regular structure and strong magnetic interactions; however, HEO exhibits capacitive behavior based on surface redox reactions and pseudo-capacitive mechanisms due to their irregular structure and oxygen vacancies. CV analyses revealed that HEO contributes more capacitive via surface redox reactions, while GCPL results suggested that HEO demonstrated superior energy density (40.8 Wh kg−1) and power density (14.3 kW kg−1). Impedance analyses revealed that HEO exhibited reduced internal resistance and enhanced ion conductivity, whereas HEA demonstrated higher resistance and diffusion-controlled processes. In conclusion, HEA and HEO exhibit distinct energy storage mechanisms, and these materials can be optimized for supercapacitor applications.
AtıfScopus36WoS34OpenAlex18İncele - MakaleAçık Erişim2025Scopus SJRQ2Multiscale Time Series Modeling in Energy Demand Prediction: A CWT-Aided Hybrid Model
Sezer, Elif; Yıldırım, Güngör; Özdemir, Mahmut Temel
In the contemporary energy landscape, the increasing demand for electricity and the inherent uncertainties associated with the integration of renewable resources have rendered the accurate and reliable forecasting of short- and long-term demand imperative. Energy demand forecasting, fundamentally a time series problem, can be inherently complex, nonlinear, and multi-scale. Therefore, interest in artificial intelligence–based methods that provide high performance for short- and long-term forecasting, rather than traditional methods, has increased in order to solve these problems. In this study, a hybrid artificial intelligence model based on LSTM, GRU, and Random Forest, utilizing a distinct mechanism to address these types of problems, is proposed. The Multi-Scale Sliding Window (MSSW) approach was utilized for the model’s input data to capture the dynamics of the time series at different scales. The optimization of windows was conducted using the Continuous Wavelet Transform (CWT) method to determine the optimal window sizes within the MSSW structure in a data-driven manner. Experimental studies on Panama’s real energy demand data from 2015 to 2020 show that the CWT-aided MSSW-hybrid model forecasts better with lower error rates (0.007 MAE, 0.009 RMSE, 1.051% MAPE) than single models and manually determined window sizes. The results of the study demonstrate the importance of hybrid structures and window optimization in energy demand forecasting.
AtıfScopus1OpenAlex2İncele - MakaleYalnız künye2025Scopus SJRQ1The Extraction of Rare-Earth Elements (REEs) from Spent Nickel–Metal Hydride (Ni–MH) Batteries by Bifunctional Ionic Liquids (Bif-ILs): Process Optimization and Kinetics Modeling
Erust, Ceren
The cathode material of nickel–metal hydride (Ni–MH) batteries includes nickel, cobalt, and rare-earth elements (REEs) such as La, Ce, Nd, and Pr, which are among the critical raw materials (CRMs). Ionic liquids as the environmentally friendly approaches are proposed by various investigations for the extraction of critical metals from spent Ni–MH batteries. In this study, three different Bifunctional Ionic Liquids (Bif-ILs) were designed for comparative studies, namely Aliquat 336–Cyanex 272 (AL–CY), Aliquat 336–PC88A (AL–PC), and Aliquat 336–D2EHPA (AL–D2). The extraction results indicated that temperature has a direct effect on the extraction of critical metals in the presence of all Bif-ILs. Among three types of Bif-ILs, AL–D2 has an optimal extraction power (La: 98.8%, Ce: 94.2%, Nd: 99.2%, and Pr: 98.4%) after precipitation of 99.99% of Ni and Co. Furthermore, kinetics modeling is used for reaction mechanisms investigation. Results indicated that the mixed controlled model by shrinking core model (diffusion controlled and chemical reaction controlled) was the best model fitted to all data (coefficient of determination (R2) > 0.90). according to the Arrhenius equation, activation energies for all REEs in the presence of all Bif-ILs are between 13 and 42 kJ/mol that reflects a mixed controlled reaction.
AtıfScopus2OpenAlex2İncele - MakaleYalnız künye2025Scopus SJRQ1Evaluation of TiO2/ZnO/SnO2 multilayer thin films on Si(100) as triboelectric friction layer
Yüzüak, G. Durak; Yüzüak, E.
This study presents a novel multilayer-semiconductor triboelectric nanogenerator (MLSC-TENG) that enhances charge transfer and initial charge density to overcome the limitations of conventional TENGs by multilayer thin films composed of TiO2, ZnO, and SnO2. The device operates through contact electrification and electrostatic induction, featuring two distinct electrodes. The active negative layer is deposited on Si substrates with an Ag seed layer using magnetron sputtering, employing a PET/ITO counter-electrode. The system attains a maximum power density of 400 mW/m2 with a 100 MΩ load, a short-circuit current of 20 μA at 10 Hz, and an open-circuit voltage of ±55 V. Additionally, it powers 156 LEDs and exhibits an energy storage capacity of 16.9 μJ at 52 μF, highlighting its applicability for wearable electronics. This scalable and cost-effective approach highlights the significant role of semiconductor (SC) band structures in enhancing TENG performance and presents a viable pathway for sustainable energy harvesting. The demonstrated strategy has the potential to meaningfully influence the application of TENGs in energy harvesting systems, providing a cost-effective solution for powering wearable electronics. The study facilitates progress in sustainable energy solutions for future wearable technologies by tackling critical issues in energy conversion efficiency.
AtıfScopus2WoS3OpenAlex3İncele - MakaleAçık Erişim2025Scopus SJRQ3Experimental and Theoretical Study on the Freshwater Productivity of a Single-Slope Solar Still
Tuğan, Volkan; Işık, Erdem; İnallı, Mustafa
Converting saline water into freshwater using renewable energy resources is crucial to address global shortages of freshwater. This study aims to investigate the freshwater productivity of a single-slope solar still (SSS) operating with solar energy, one of the renewable energy sources. The main motivation of this study is to evaluate the experimental, theoretical, and economic performance of the solar still under climate conditions that have not been sufficiently studied before. Experimental analyses were conducted under the climatic conditions of Tunceli, a city located in the Eastern Anatolia Region of Türkiye. In addition, a comprehensive theoretical analysis was carried out using energy equations, and the experimental and theoretical results were compared with each other. Finally, the economic feasibility of the system was evaluated through a cost analysis. The SSS's experimental and theoretical productivity were found to be 1883.9 and 2458.7 g/m2/day, respectively. The experimental thermal efficiency for this still was 15.1%, whereas the theoretical thermal efficiency was 19.7%. It was concluded that the theoretical productivity and efficiency values were close to the experimental values and the difference between them originated from the assumptions of theoretical calculations. The cost of water distilled by the single-slope solar distillation unit was found to be $0.077/kg, and the payback period was found to be 9 months.
AtıfScopus2WoS3OpenAlex2İncele
