Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Araz, Onur(15)
- Ozturk, Samet(14)
- Ozyurt, E.(9)
- Turk, Veysel(9)
- Reis, Hatice Catal(7)
- Beder, Murat(6)
- Erdogdu, Ferruh(6)
- Peker, Iskender(6)
- Erol, Ismail(5)
- Kaygusuz, Abdullah(5)
- Ozturk, Kasif Furkan(5)
- Wang, Y.C.(5)
- Akpinar, Adem(4)
- Akçay, Serhatcan Berk(4)
- Coskun, Eda(4)
- Kankal, Murat(4)
- Kaya, Selim(4)
- Liu, Shuxiang(4)
- Ozden, Talat(4)
- Seferoğlu, Mehmet Tevfik(4)
- Varol, Temel(4)
- Öztürk, Serkan(4)
- Akinoglu, Bulent G.(3)
- Alemdag, Selcuk(3)
- Arslan, Mehmet(3)
- Cakir, Tufan(3)
- Gurocak, Zulfu(3)
- Gücer, Mehmet Ali(3)
- Günen, Mehmet Akif(3)
- Kaya, Ali(3)
- Mert, Behic(3)
- Mızrak, Sefa(3)
- Saydam Eker, Çiğdem(3)
- Tasci, Caner(3)
- Çelik, Necati(3)
- Ünlü, Ramazan(3)
- Şan, Murat(3)
- Akpinar, A.(2)
- Akpinar, Merve(2)
- Aksa, Hüseyin Can(2)
Yayınlar
- MakaleAçık Erişim2025A strategy for the one-pot direct production of 5-hydroxymethylfurfural (HMF) from sucrose using organic weak acid in situ as a catalyst
Gül, Abdulkadir; Tanyıldızı, Muhammet Şaban
5-Hydroxymethylfurfural (HMF), which can be produced in high yields by acid-catalyzed dehydration of carbohydrates, is used as a feedstock in biofuel and biopolymer production. However, these acidic catalysts are usually added externally, which increases HMF production costs. Furthermore, other important parameters for high yields of HMF production are raw material selection, reaction medium, and separation-purification processes. The aim of this study is to produce HMF in one-pot without the addition of any exogenous catalyst by evaluating the fructose remaining in the production medium in which the glucose from sucrose hydrolysis is microbially fermented into gluconic acid (GA). HMF production from fructose in a biphasic system consisting of a fermentation liquid containing GA and fructose and 2-Methyltetrahydrofuran (2-MeTHF) was optimized using Central Composite Design (CCD). The variables examined included reaction time, reaction temperature, solvent type, salt type, and organic/aqueous phase ratio. In the study, by chelating GA and calcium ions, the low degree of ionization of GA was increased, and HMF was produced in high yields without the addition of a catalyst. Under optimum conditions, using 2-MeTHF/ fermentation liquid (6:1) and 7.56 wt% CaCl2, the yield of HMF produced in pressurized (hydrothermal) vessels at about 147 °C for 158 min reached 77.6 % of the theoretical yield. The amount of GA in the production medium was 92.64 % preserved from degradation. GA and HMF in different phases of the biphasic system were purified from the production medium in high yields. Furthermore, 2-MeTHF, which constitutes the organic phase of the biphasic system, was recovered at approximately 95 % by vacuum evaporation. As a result, HMF production from sucrose, which is a more economical and abundant raw material compared to glucose and fructose, was realized in one-pot without the addition of any catalyst.
- MakaleYalnız künye2025Performance evaluation and optimization of nontraditional inerter-based tuned mass damper for seismic control of multi-story buildings considering SSI effects
Araz, Onur
This article presents the optimum design and performance evaluation of a control system that can be an alternative to traditional inerter-based tuned mass damper (TMDI) used in reducing vibrations in a multi-story building under earthquake effects considering soil-structure interaction (SSI). The optimum design of this system, known as NIDVA-C4 in the literature, has been carried out previously considering the randomly excited undamped main system. The key novelty of this work is to demonstrate the applicability of this system to suppress earthquake-induced vibrations in a multi-story building and to deliver more accurate and reliable results by integrating SSI effects into the optimization framework. Due to the difference in location and connection, this system is called N-TMDI in this paper. A case study from the literature featuring a ten-story building is used to implement the design process, assess performance, and conduct comparisons. The optimum parameters of the N-TMDI are obtained using the hybrid PSO-SA algorithm in the frequency domain. Validation using real earthquake records under varying soil conditions confirms the reliability of the proposed optimization framework. The coupled dynamic equations of motion for the structure - N-TMDI, accounting for SSI effects, are formulated and solved in the time domain using the Newmark-β method. An extensive parametric analysis is conducted to evaluate the effectiveness of the N-TMDI in improving the seismic response of the buildings. The results consistently demonstrate the effectiveness of the proposed protection strategy across a wide range of parametric configurations, highlighting its potential as a viable seismic mitigation strategy for a multi-story building.
- MakaleAçık Erişim2025Towards precision dentistry through artificial intelligence and blockchain-based digital Twins: Investigating challenges and solution strategies
Erol, Ismail; Peker, Iskender; Medeni, Ihsan Tolga; Yuce, Fatma
The integration of artificial intelligence (AI), blockchain, and digital twins (DT) in dentistry is essential to meet evolving patient expectations and global healthcare challenges. However, realizing their full potential requires addressing significant adoption barriers. While conceptual studies have explored challenges to implementing AI, blockchain, and DT in dentistry, no prior research has systematically analyzed the interrelationships among these obstacles using a structured decision framework. This study employs pentagonal fuzzy (PF) DEMATEL to investigate the connections among challenges to effectively implementing AI and blockchain-based DT in dentistry. Expert opinions highlight ethical considerations and bias and fairness in AI-based DT as the most critical causal challenges. We propose an AI and blockchain-based DT architecture that enables human doctors to leverage DT-based decision support, while AI-driven systems execute high-precision procedures with blockchain-verified workflows. This framework enhances treatment accuracy and personalization in dentistry and offers a scalable model for addressing societal concerns, such as privacy, fairness, and labor dynamics, in technology-driven ecosystems. A pilot study framework is proposed to validate diagnostic accuracy, data security, and treatment customization. Accompanied by stakeholder guidelines, this research bridges dentistry with broader discussions on technology's societal impact, emphasizing the need for interdisciplinary strategies to ensure equitable and trustworthy innovation.
- MakaleYayıncıda açık erişim2025A quantitative analysis on the effect of crystal parameters on full energy peak efficiency of a coaxial high purity Germanium detector for the energy range 50 keV-2.5 MeV
Çelik, Necati
High Purity Germanium (HPGe) detectors are essential instruments in gamma-ray spectrometry, offering high sensitivity and exceptional energy resolution. The full-energy-peak (FEP) efficiency is a critical parameter that influences the accuracy of activity concentration measurements of radionuclides. This study examines the FEP efficiency of a coaxial HPGe detector, focusing on variations in crystal length, crystal radius, and crystal hole dimensions. For varying crystal lengths, the efficiency values show negligible differences at low energy (50 keV) but significant increases at higher energies, indicating that longer crystal lengths enhance efficiency. Similarly, the efficiency increases with larger crystal radii across all energy levels suggesting substantial efficiency gains even at low energies. However, variations in crystal hole radius and depth, exhibit minimal impact on FEP efficiency across all tested energy levels. These findings highlight that optimizing crystal length and radius is more crucial for changing detector efficiency compared to modifying hole dimensions, providing valuable insights for optimizing Monte Carlo models and detector design.
- MakaleAçık Erişim2025Incorporation of ultrasound-assisted treatment in cheese to accelerate ripening of Kaşar cheese: Changes in cheese microbiota, proteolysis, enzyme activities and volatile profiles
Yılmaz, Fırat; Dağdemir, Elif; Hayaloğlu, Ali Adnan
This study aimed to assess the impact of using LAB strains (Lactobacillus helveticus DPC 4571 and Lactobacillus casei ATCC 334) directly or after sonication on the quality and ripening of Kaşar cheese. Experimental cheeses were produced with a combination of cheese starters (Streptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus), adjuncts and sonicated cultures. The cheeses showed remarkable variations in titratable acidity and pH. The bacterial counts showed that sonication was effective on adjunct cultures, causing faster and stronger autolysis of L. helveticus DPC 4571 and an increase in L. casei ATCC 334 during ripening. Cheeses containing adjunct cultures exhibited higher proteolysis, with increased hydrolysis of αs1- and β-caseins. Aminopeptidases activities increased during ripening by adjuncts and sonicated-adjunct cultures. The use of adjunct culture resulted in a greater increase in the free amino acid content. Adjuncts and sonicated-adjunct cultures increased both the quantity and diversity of some volatiles. In conclusion, the inclusion of sonicated culture in the starter system offered a potential approach to accelerate cheese ripening and improve cheese quality.
- MakaleAçık Erişim2025Investigation of the effects of mainshock-aftershock sequences on the dynamic responses of pipeline considering soil-pipeline interaction
Ozturk, Kasif Furkan
Pipelines are important structural elements that are frequently used today to meet many infrastructures needs such as drainage, natural gas or water transmission. In this context, the usability of such structures, which are important elements of infrastructure systems, especially after disasters such as earthquakes, is of great importance. For this reason, within the scope of this study, a parametric investigation of the seismic behaviors of a natural gas pipeline system under mainshock-aftershock sequences have been carried out, specifically taking into account the soil-natural gas pipeline interaction (SNGPI) in the help of finite element model (FEM) proposed. Before developing the model of SNGPI system proposed using solid element, the fundamental mode frequencies of the pipeline system modeled using the solid element for the verification have been compared with those of obtained from the pipeline system modeled using the beam element and the analytical solutions. After verification of proposed model is demonstrated, SNGPI system has been modeled and its fundamental modes have been compared with mode frequencies of soil stratum obtained from well-known simple analytic solutions. After this stage, the dynamic analyses of natural gas pipeline (NGP) system in the time domain have been carried out using four different soil systems and four different mainshock-aftershock sequences. The results of the nonlinear time-history analyses have been investigated in terms of the stress and the displacement responses. Parametric evaluations show that the greatest displacements and the stresses occurring at the considered nodes of NGP system may be importantly affected from mainshock-aftershock sequences and soil stiffness changes. As the soil stiffness decreases, both the peak stresses and displacements increased significantly. On the other hand, the same responses obtained under mainshock loadings, which have relatively lower peak ground acceleration (PGA)/peak ground velocity (PGV) ratio compared to aftershock loadings, are generally larger than those obtained under aftershock loadings.
- MakaleAçık Erişim2025Effect of basic parameters defining principal soil-structure interaction on seismic control of structures equipped with optimum tuned mass damper
Araz, Onur
One of the most effective systems for reducing dynamic responses of the structures subjected to earthquake excitations is tuned mass dampers (TMDs). In the traditional design theory of TMDs, the structures are assumed to be rigidly connected to the ground. Using this approach, known as the fixed foundation approach, may lead to deterioration of the performance of the TMD in cases where soil-structure interaction (SSI) is significant. Therefore, it is crucial to consider the SSI effects to obtain the optimum parameters of the TMDs. Unlike previous studies, two key parameters (i.e., structure-to-soil stiffness ratio and aspect ratio of the structure) are considered, which define the principal SSI effects on the effectiveness of TMD. For the aspect ratio of the structure, three different values (i.e., λ = 1, 2, and 4) are considered, these values correspond to the squat, ordinary, and slender structures representing traditional buildings, respectively. Four different values (i.e., a0 = 0, 0.5, 1, and 2) are also considered for the structure-soil stiffness ratio. This ratio being equal to 0 corresponds to the fixed foundation approach. This also demonstrates that the structure is constructed on hard rock. The optimum parameters of the TMD are obtained using the Jaya algorithm (JA). The proposed methodology is applied to three different buildings (i.e., 3-story, 6-story, and 12-story), and the optimum parameters of the TMD are verified using a total of 72 ground motions corresponding to NEHRP site classes C, D, and E. Numerical results show that the effectiveness of TMD is significantly affected by the basic parameters that define the principal SSI. In addition, the efficiency of the TMD is significantly related to the characteristics of the ground motions. It has been observed that TMD does not perform adequately in reducing vibrations in low-rise buildings (i.e., λ = 1) constructed on low-stiffness soils (i.e., a0 = 2).
- MakaleAçık Erişim2025Characterization of thermal, chemical, mechanical, and fatigue behavior of 3D printed ABS-based elastomeric blends: ABS/EVA and ABS/TPU
Kuleyin, Hamdi; Budak, Selahattin; Yasan, Ömer Barışkan; Gümrük, Recep
The polymer blending method is widely used to obtain balanced mechanical properties and structural performance in many engineering applications. This study investigates the influence of Ethylene-Vinyl Acetate (EVA), and Thermoplastic Polyurethane (TPU) composition ratios on the thermal, chemical, viscoelastic, mechanical, and fatigue life behavior of Acrylonitrile-Butadiene-Styrene (ABS) based elastomeric blends. For this purpose, structural and mechanical properties of the blend material depending on their composition ratio were carried out through a series of characterization analyses, and tensile and fatigue tests. The findings indicated that ABS/EVA and ABS/TPU blends formed an immiscible structure. In addition, it was determined that the storage modulus of the blend with 10 % TPU improved because of the presence of new absorption peaks in the structure. The mechanical properties such as elastic modulus, yield strength, and ultimate tensile strength decreased concerning neat ABS with an increase in the EVA and TPU composition ratio for blend materials. However, the elongation to break was achieved approximately 6 times increasing with an increase in the TPU ratio for ABS/TPU blends. It was determined that the fatigue strength value in ABS/EVA and ABS/TPU blends decreased with the decrease in ABS composition ratio in the blend system. However, it was found that fatigue life improved by 25 % compared to ABS at low-stress amplitude for 10 % TPU additive. Finally, it can be revealed that the ABS-based elastomeric blends can be used to obtain desired properties according to their composition ratios for different applications.
- MakaleAçık Erişim2025DSCIMABNet: A novel multi-head attention depthwise separable CNN model for skin cancer detection
Reis, Hatice Catal; Turk, Veysel
Skin cancer is a common type of cancer worldwide. Early diagnosis of skin cancer can reduce the risk of death by increasing treatment success. However, it is challenging for dermatologists or specialists because the symptoms are vague in the early stages and cannot be noticed by the naked eye. This study examines digital diagnostic techniques supported by artificial intelligence, focusing on early skin cancer detection and two methods have been proposed. In the first method, DSCIMABNet deep learning architecture was developed by combining multi-head attention and depthwise separable convolution techniques. This model provides flexibility in learning the dataset's local features, abstract concepts, and long-term relationships. The DSCIMABNet model and modern deep learning models trained on ImageNet are proposed to be combined with the ensemble learning method in the second method. This approach provides a comprehensive feature extraction process that will increase the performance of the classification process with ensemble learning. The proposed approaches are trained and evaluated on the ISIC 2018 dataset with image enhancement applied in preprocessing. In the experimental results, DSCIMABNet achieved 84.28% accuracy, while the proposed hybrid method achieved 99.40% accuracy. Moreover, on the Mendeley dataset (CNN for Melanoma Detection Data), DSCIMABNet achieved 92.58% accuracy, while the hybrid method achieved 99.37% accuracy. This study may significantly contribute to developing new and effective methods for the early diagnosis and treatment of skin cancer.
- MakaleAçık Erişim2025The effect of high B4C ratio on the improvement of mechanical properties and wear resistance of Al2024/B4C composites fabricated by mechanical milling-assisted hot pressing
Beder, Murat
In this study, the effects of 0 wt% (C0), 10 wt% (C1), 20 wt% (C2) and 40 wt% (C3) B4C content on the microstructure, mechanical properties and dry wear properties of Al2024/B4C composites were investigated. In order to prepare Al2024 matrix composites with different B4C particle contents, mechanical milling (MM) and hot pressing (HP) were employed as powder metallurgy methods. It was found that the θ (CuAl2) phase content in the microstructure of Al2024/B4C compact materials increased with increasing B4C particle reinforcement, reaching its highest value at 40 wt% B4C (C3) reinforcement ratio. As the B4C particle reinforcement content increased, the hardness values of the composite samples increased. Flexural strength values were 445.30 MPa, 495.20 MPa, 277.59 MPa, and 129.37 MPa for samples coded C0, C1, C2, and C3, respectively. It was found that the C0 sample without particle reinforcement exhibited more than 10 times the volume loss of the C3 sample with the highest particle reinforcement at 450 m sliding distance. The SEM examination of the friction surfaces of the Al2024/B4C composite samples showed that the worn surfaces were composed of delamination, adhesion and smearing layers.
- MakaleAçık Erişim2025Advancing sea level anomaly modeling in the black sea with LSTM Auto-Encoders: A novel approach
Yavuzdoğan, A.; Tanir Kayıkçı, E.
Rising sea levels pose significant risks to coastal communities and ecosystems. Accurate modeling of sea level changes is crucial for effective environmental management and disaster mitigation. Machine learning methods are emerging as an important asset in improving sea level predictions and understanding the impacts of climate change. Especially, Long Short-Term Memory (LSTM) models have emerged as a powerful tool for sea level anomaly modeling, but there is an increasing need for more advanced models in this area. This study enhances existing methodologies by introducing a novel approach using an LSTM Auto-Encoder model, designed to compress input data into a lower-dimensional latent space before reconstructing it, thereby capturing complex temporal dependencies and anomalies effectively. We compared LSTM Auto-Encoder model performance with that of a Stacked LSTM network, which learns complex temporal patterns through multiple layers, and a traditional damped-persistence statistical model. Our results demonstrate that the LSTM Auto-Encoder model not only outperformed these models in predicting sea level anomalies across various lead times but also exhibited superior generalization capabilities across both satellite altimeter and in-situ data. These findings highlight the potential of the LSTM Auto-Encoder model as a powerful tool in coastal management and climate change studies, underscoring the critical role of advanced machine learning techniques in enhancing our predictive abilities and informing disaster preparedness strategies.
- MakaleYalnız künye2025Influence of PGA/PGV ratio on the seismic performance of buildings with different slenderness ratios considering soil-structure interaction
Araz, Onur
In this study, the seismic performance of buildings equipped with tuned mass damper (TMD) having different slenderness ratios, subjected to ground motions with varying a wide range of PGA/PGV ratios is investigated, considering soil-structure interaction (SSI). A methodology based on hybrid Genetic Algorithm-Particle Swarm Optimization (GA-PSO) algorithm is proposed to determine the optimal parameters of TMD. For this purpose, three buildings (i.e., 3-story, 6-story, and 12-story buildings) are considered and the dynamic properties of these buildings are determined according to the provisions specified in ASCE-7. These buildings, which are frequently encountered in the traditional building stock, represent low, medium, and high-rise buildings, respectively. In the numerical analysis, three different soil types (i.e., SC, SD, and SE) and 80 ground motions are also considered. These records are divided into three different classes: high, intermediate, and low frequency content. The Newmark integration method is used to determine the dynamic responses of the structures in the time domain analysis. Numerical results show that the frequency content of ground motion and the slenderness ratio have a significant effect in reducing the peak displacement and acceleration responses of structures. The findings also demonstrate that when the PGA/PGV ratio is greater than 2, TMD shows mostly sufficient control performance for all buildings and all support conditions.
- MakaleAçık Erişim2025Agrivoltaic system design for sugar beets and wheat in central Anatolia
Yalçın, Ömer; Kuzyaka, Duygu; Özden, Talat
Agrivoltaic systems, which integrate photovoltaic (PV) panels with the usage of agricultural land, emerge as a promising strategy by facilitating the simultaneous generation of renewable energy alongside the cultivation of various crops within the same area. This research is centered on the design and implementation of an agrivoltaic system that is specifically customized for the cultivation of wheat and sugar beet in the Central Anatolia Region of Turkey. The primary objective of this research is to optimize the spatial arrangement of the PV panels to achieve a balance between the generation of energy and the productivity of the crops. Through a detailed assessment of shading effects and Photosynthetic Photon Flux Density (PPFD) levels, this investigation will endeavor to unravel the complex interplay between panel configuration and its consequential impacts on both plant growth and energy output. In this investigation, the shading impacts attributed to three distinct configurations—specifically, the conventional solar power plant (SPP), the intermittently arranged panel layout, and the intermittently arranged V-shaped panel configuration—were assessed, and their appropriateness for the cultivation of wheat and sugar beet was evaluated. The V-shaped design, which additionally facilitates rainwater collection, yielded an enhanced PPFD value across the three designated regions beneath the panels.
- MakaleYayıncıda açık erişim2025Chrome waste utilization in base layers: Mechanical strength and environmental risk assessment
Seferoğlu, Mehmet Tevfik; Acı, Elif Nur
This study investigates the partial substitution of natural aggregate (Na) with chrome mine waste (Crw) in highway base layers, focusing on mechanical performance and environmental safety. Crw-Na mixtures with contents from 0 % to 100 % were tested using CBR, cyclic plate loading, chemical, and leachate tests. The 15 % Crw-85 % Na mixture achieved the highest CBR (287.4 %) with limited deformation (37 mm). Although the 60 % Crw blend also met the required strength level (156.6 %), it showed higher settlement (50 mm) and three times greater vertical strain. SEM-EDX and chemical results indicated increased magnesium content and mineral changes at higher Crw ratios. Leachate tests confirmed compliance with TS266 and international water standards; all samples were categorized as neutral drainage with low metal risk. The findings show that Crw improves strength without causing environmental risk. Among tested mixtures, 15 % Crw offered the most balanced outcome in terms of field stability and performance.
- MakaleYalnız künye2025Spatial and temporal patterns of drought under different scenarios for Türkiye in the 21st century
Yıldız, Mehmet Berkant; Nacar, Sinan; Şan, Murat; Kankal, Murat
This study investigates the impact of climate change on drought conditions in Türkiye for two distinct future periods: the near future (2021–2050) and the far future (2071–2100), under two emission scenarios (RCP4.5 and RCP8.5). High-resolution regional climate projections from 19 GCM-RCM combinations within the EURO-CORDEX framework were evaluated. Based on performance analysis against ERA5-Land data, the four best-performing models were selected for multi-model ensemble averaging (MMEA). Drought conditions were assessed using the Standardized Precipitation Index (SPI) at 3-, 6-, and 12-month time scales. Three trend analysis methods, Innovative Trend Analysis (ITA), Modified Mann-Kendall (MMK), and Sen's Slope, were applied to examine spatiotemporal drought patterns. SPI-based analyses show a significant increase in short- and medium-term variability (SPI-3 and SPI-6) and long-term droughts (SPI-12), especially in the Central Anatolia, Southeastern and Eastern regions. The applied trend detection methods consistently point to a widespread drying tendency, with more pronounced changes projected in the latter half of the century. Under the RCP4.5 scenario, although the drought signals are less severe, the persistence of negative trends highlights that Türkiye will still be at risk, even with moderate efforts to mitigate climate change. These findings underscore the urgent need for integrating climate-driven drought projections into national and regional planning efforts.
- MakaleAçık Erişim2025A multi-stage fusion deep learning framework merging local patterns with attention-driven contextual dependencies for cancer detection
Catal Reis, Hatice; Turk, Veysel
Cancer is a severe threat to public health. Early diagnosis of disease is critical, but the lack of experts in this field, the personal assessment process, the clinical workload, and the high level of similarity in disease classes make it difficult. In recent years, deep learning-based artificial intelligence models have shown promise, with the potential to increase diagnosis speed and accuracy. These models attract attention with their automatic learning and adaptation capabilities. In this study, the deep learning-based PADBSRNet model and the PADBSRNet-Vision Transformer (ViT) hybrid method are proposed for the detection of brain tumors and skin and lung cancers. PADBSRNet is a comprehensive deep neural network architecture that integrates separable and traditional convolution layers, multiple attention mechanisms, bidirectional recurrent neural networks, and cross-connections/multi-stage feature fusion strategies. This architecture offers significant advantages in terms of effectively extracting local-global, contextual features and accurately modeling long-term dependencies in image classification tasks. The second proposed approach developed a hybrid method that combines the advantages of the PADBSRNet model and the ViT model. Experimental analysis on medical datasets such as the Figshare Brain Tumor Dataset, IQ-OTH/NCCD Dataset, and Skin Cancer: Malignant vs. Benign Dataset has evaluated the proposed models' performances. According to the experimental results, the PADBSRNet model has shown successful performance with 95.24 %, 99.55 %, and 88.61 % accuracy rates, respectively. The experimental findings show that the proposed deep learning model can effectively learn the complex relationships and hidden patterns of cancer disease, thus producing applicable and effective results in cancer diagnosis.
- MakaleYalnız künye2025Concentrations, distribution, and source appointment of heavy metal/loids in non-clastic sedimentary rocks: a case study of early jurassic chert, northeastern türkiye
Saydam Eker, Çiğdem; Kaygusuz, Abdullah; Arı, Uğur Volkan
The Current study used geochemical indicators such as the geo-accumulation index (Igeo), the Enrichment Factor (EF), and the contamination factor (CF) to evaluate the regional distributions and accumulations of various heavy metal/loids (HM; Co, Mo, Pb, Zn, Cu, Ni, As, Cd) in early Jurassic cherts in the Gümüşhane (NE Türkiye). Five stratigraphic section measurement (MS) areas (Tedaş, Alemdar, Akçakale, Tekke, and Pirahmet) and one borehole (Eskibağlar well) were selected for sampling. Major and trace element compositions of the selected 25 samples were measured by inductively coupled plasma optical emission spectrometry (ICP-OES) and inductively coupled plasma mass spectrometry (ICP-MS). Calculated geochemical indexes indicated that Alemdar, Tekke MS, and Eskibağlar well samples were polluted with Pb, Zn, Cu, As, and Cd, Tedaş, Akçakale, and Pirahmet MS samples were polluted with Cd. Pearson's correlation coefficient (PCC) and principal component analysis (PCA) suggested that Zn, Pb, and Cu contaminating the Alemdar, Tekke MS, and Eskibağlar well samples were of ore mineralization origin, As was of terrigenous input, and Cd was probably of diatom origin. PCC and PCA showed that the Cd contaminating the Tedaş, Akçakale, and Pirahmet MS samples was probably of diatom origin, and the other metals found at normal levels in the samples were due to terrigenous input. The Early Jurassic period, which was a rift environment in the Gümüşhane region, is thought to have produced the cherts of the Alemdar, Tekke MS, and Eskibağlar well samples in a graben environment, while the cherts of the Tedaş, Akçakale, and Pirahmet MS were deposited in a horst environment. δU values, Ni/Co, and Vi/(V + Ni) ratios indicated that oxic-anoxic conditions were generally prevalent in the depositional environment, but redox conditions did not affect the abundance and distribution of HMs. These findings provide critical information for assessing heavy metal/loid enrichment and contamination potential not only in clastic sedimentary rocks, river sediments, and soils but also in non-clastic sedimentary rocks.
- MakaleYalnız künye2025Application of SnO2@CTAB-modified zeolitic clay nanocatalyst for the efficient sonocatalytic degradation of methylene blue in wastewater: Structural characterization, catalytic activity, and mechanistic insights
Önen, Hakan; Kıranşan, Murat
This study investigates the sonocatalytic degradation of dyes in wastewater using SnO2 nanoparticles and a hybrid SnO2@CTAB-modified zeolitic clay (SnO2@M-ZLT) nanocatalyst. The catalysts were synthesized in solution medium and characterized by XRF, XRD, FT-IR, SEM, TEM, and nitrogen adsorption-desorption analyses, confirming their successful formation and suitable surface properties. The effects of critical parameters including initial dye concentration, catalyst dosage, pH, water matrix, and radical scavengers on the removal of methylene blue (MB) were systematically evaluated. Under optimal conditions (10 g L−1 catalyst, 10 mg L−1 MB, Ultrasonic power: 300 W/L, pH for MB: Natural pH), the SnO2@M-ZLT nanocatalyst achieved 97.40 % ± 1.12 % degradation within 120 min, while 95.05 % ± 1.25 % efficiency was observed at 5 g L−1 catalyst and 5 mg L−1 MB. The sonocatalytic degradation of MB over SnO₂@M-ZLT followed pseudo-first-order kinetics, with kapp values ranging from 0.004 to 0.082 mg L−1 min−1 depending on catalyst dosage, 0.012–0.083 mg L−1 min−1 with varying MB concentration, and 0.030–0.055 mg L−1 min−1 across different water matrices. The optimal degradation efficiency was obtained at a catalyst dosage of 2–2.5 g L−1, an initial MB concentration of 5–10 mg L−1, and in distilled water, confirming the strong dependence of the reaction rate on both operational and environmental factors. Reusability tests showed that SnO2@M-ZLT retained high catalytic activity after five cycles. These results highlight the strong potential of SnO2@M-ZLT as an efficient and stable nanocatalyst for sustainable wastewater treatment.
- MakaleYalnız künye2025Influences of chord pre-stress on CHS X-joints with high-strength-steel at various temperatures
Ozyurt, E.; Wang, Y.C.
This study examines the influence of chord pre-stress on the behaviour and load resistance of Circular Hollow Section (CHS) X-joints with High Strength Steel (HSS) at various temperatures. This investigation uses a total number of seven hundred and four Finite Element simulation results to evaluate the level of accuracy of current Eurocode and CIDECT design guidelines in predicting the high-temperature resistance of these joints. The numerical simulations investigate the effects of changing brace-to-chord diameter (β), chord semi-diameter-to-thickness (γ), and brace-to-chord thickness (τ) ratios, as well as different prestressing levels (np) and temperatures (θ). The γ and τ ratios have a limited effect on the normalised joint strength, but the β ratio, and the prestressing level are highly influential. At ambient temperature, the CIDECT design approach is a more suitable method for calculating the chord pre-stress reduction factors for S355 joints. For HSS X-joints, the constant modification coefficient of 0.80 is inadequate, and this paper has proposed a new modification coefficient as a function of the pre-stress level. At elevated temperatures, the ambient temperature resistance of CHS X-joints can be modified by the reduction factor of the Young's modulus for S355 steel and that of the yield stress for S960 steel.
- MakaleYalnız künye2025Characterization, corrosion, adhesion and wear properties of Al2O3 and Al2O3:TiB2 composite coating on Al 7075 aluminum alloy by one-step micro-arc oxidation method
Sukuroglu, Suleyman
This study was carried out in order to increase the usage areas of Al 7075 alloy, which is preferred as an engineering material in the aerospace industry, defense industry and automotive industry, in high temperature applications, wear resistance in different environments and corrosion resistance in aggressive environments. For this purpose, the focus was on the growth of Al2O3 and Al2O3:TiB2 doped composite coatings on the surface of Al 7075 aluminum alloy by the MAO method, and the structural, morphological, corrosion, adhesion and wear properties of the grown coatings in three different environments (atmospheric conditions, brine containing 3.5 % NaCl and oil). Firstly, Al2O3 coatings were grown in electrolytic solution number 1. Secandly, Al2O3:TiB2 doped composite coatings were grown in electrolytic solution number 2 and the phase structure, microstructure and chemical composition of the grown coatings were determined by X-ray Diffraction, Scanning Electron Microscopy, Energy Dispersive X-ray Spectroscopy, respectively. The abrasion behavior of the coatings in three different environments was determined by a pin-on disc abrasion tester, adhesion resistances were determined by a Scratch Test, and corrosion resistance was determined by a potentiodynamic polarization tester. It was observed that dense and uniform coatings were grown on the surfaces of TiB2 nanoparticle-added (Al2O3:TiB2) coatings, porosity and pore sizes on the surfaces of the coatings were reduced and microcracks were reduced. In addition, it was determined that the corrosion resistance and wear resistance of composite coatings (Al2O3:TiB2) grown with nanoparticle addition increased, and coatings with high bond strength with the substrate were grown.