Yazar "Arslanoglu, Hasan" seçeneğine göre listele

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    Antibacterial efficacy of pyrolysis-derived plant fractions against resistant pathogens: a comparative evaluation using nutrient and Müller-Hinton agar
    (Wiley, 2026) Demirel, Maruf Hursit; Gul, Abdulkadir; Aydogmus, Ercan; Ozgen, Inanc; Arslanoglu, Hasan
    BACKGROUND This study investigates the antibacterial potential of pyrolysis-derived extracts from rosehip fruit (RF), orange peel (OP), corn silk (CS), spurge root (ER) and mullein leaf (ML) against antibiotic-resistant pathogens using two different culture media. Bioactive compounds were obtained via a PID-controlled pyrolysis system, and antibacterial activity was evaluated to clarify both extract efficacy and medium-dependent effects on bacterial growth and diffusion.RESULTS Antibacterial activities were assessed using the agar well diffusion method, with ampicillin as a positive control, against Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus and Enterococcus faecalis. A key novelty of this work is the comparative evaluation of extract performance on nutrient agar (NA) and M & uuml;ller-Hinton agar (MHA). Among all samples, the ML extract exhibited the strongest antibacterial activity across all tested strains, producing inhibition zones of 18.85 mm against E. coli and 17.15 mm against E. faecalis on NA, compared with 13.05 mm and 13.60 mm on MHA, respectively. CS and ER extracts showed moderate antibacterial effects, with consistently higher inhibition zones on NA than on MHA. Ampicillin generated substantially larger inhibition zones on NA (33.35 mm for E. coli and 34.45 mm for P. aeruginosa) compared with MHA (13.80 and 27.70 mm, respectively), confirming the strong influence of culture medium composition on measurable antibacterial activity.CONCLUSION These results indicate that both plant extracts and ampicillin exhibit higher antibacterial activity on NA than on MHA. The pronounced efficacy of the ML extract highlights pyrolysis-derived plant fractions as promising natural antimicrobials and emphasizes the critical importance of culture medium selection. (c) 2026 Society of Chemical Industry.
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    Chitosan-Derived Porous Carbon for Efficient Adsorptive Removal of Amoxicillin and Doxycycline Antibiotics from Aqueous Systems
    (Springer Int Publ Ag, 2025) Turk, Feride N.; Arslanoglu, Hasan
    Traditional antibiotic removal techniques-such as coagulation, membrane filtration, ozonation, and biodegradation-are often inadequate for large-scale applications due to limiting factors including high operational costs, complex system design, and the formation of toxic by-products. In addition, the low selectivity levels of these techniques and the need for additional post-treatment make it difficult to achieve effective and sustainable water treatment goals. The phosphoric acid-activated chitosan-derived carbon adsorbent proposed in this study demonstrated superior adsorption capacities for both amoxicillin and doxycycline, owing to its high surface area and abundant functional groups, aligning with sustainability principles. Thus, it stands out as an economical and environmentally friendly alternative that directly solves the shortcomings of previous methods. High-performance activated carbon was synthesized via phosphoric acid activation of chitosan for the removal of amoxicillin (AMX) and doxycycline (DOC) antibiotics from aqueous solutions. The adsorption efficiency was systematically evaluated in batch experiments at temperatures ranging from 30 to 50 degrees C, initial antibiotic concentrations of 50-400 mg/L, and pH levels spanning from 3 to 13. The phosphoric acid activation process significantly influenced the physicochemical properties of the resultant activated carbon, enhancing its structural and textural characteristics. The activated carbon exhibited a substantial surface area of 998.02 m2/g, a pore volume of 0.485 cm3/g, and an average pore diameter of 2.55 nm, structure favorable for adsorption. Furthermore, kinetic analysis revealed that the adsorption process followed the pseudo-first-order model, indicating that physisorption was the dominant mechanism. Equilibrium data were best described by the Langmuir isotherm model, highlighting monolayer adsorption on a homogeneous surface. The maximum adsorption capacities for AMX and DOC were determined to be 227.18 mg/g and 299.07 mg/g, respectively, at 50 degrees C, demonstrating the high affinity of the adsorbent for these pharmaceutical contaminants. These findings indicate that chitosan-derived activated carbon is a cost-effective, sustainable material with strong potential for removing antibiotic contaminants from wastewater.
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    Co-pyrolysis of waste tires and Platanus orientalis leaves: thermogravimetric characterization, kinetic modeling, and resource valorization potential
    (Wiley, 2026) Turk, Feride N.; Ugur, Mucahit; Arslanoglu, Hasan
    This study investigates the co-pyrolytic behavior of waste tires (WT) and Platanus orientalis leaves (SL) as hybrid feedstocks for thermochemical valorization. Pyrolysis experiments were conducted under nitrogen atmosphere using thermogravimetric analysis across a temperature range of ambient to 745 degrees C, with heating rates of 5, 10, 15, 20, and 25 K min-1. Five blend ratios (100% WT, 75/25, 50/50, 25/75, 100% SL by mass) were assessed to evaluate thermal degradation profiles and kinetic characteristics. A Box-Behnken experimental design within the response surface methodology (RSM) framework was employed to optimize the effects of temperature, heating rate, and blend ratio on pyrolysis performance. The statistical model showed a high predictive capability with R 2 >0.995. Kinetic parameters were calculated using Coats-Redfern, Flynn-Wall-Ozawa, and Kissinger methods, with activation energies for the major decomposition stage (Stage 3C) ranging from 114.3 to 125.2 kJ mol-1. A significant negative correlation was found between activation energy and SL content (r = -0.82), while WT content showed a positive correlation (r = 0.87), indicating that biomass reduces the energy barrier for thermal degradation. Fourier transform infrared analysis confirmed the breakdown of functional groups such as -OH, C-O, and aromatic C-C after pyrolysis, indicating extensive structural transformation. Scanning electron microscopy imaging revealed morphological changes from fibrous structures in SL to carbonized, fractured surfaces in the char. Energy-dispersive X-ray spectroscopy analysis indicated a high carbon content (91.2%), supporting the suitability of the product for energy applications. Overall, the study demonstrates the synergistic potential of WT and SL in co-pyrolysis, improving thermal behavior, reducing activation energy, and yielding carbon-rich products. These findings support the development of integrated waste-to-energy strategies aligned with circular economy principles.
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    Comparative analysis of artificial neural networks and adaptive neuro-fuzzy inference system for biocomposite material synthesis and property prediction
    (Elsevier Science Sa, 2025) Aydin, Muhammet; Aydogmus, Ercan; Arslanoglu, Hasan
    Biocomposite materials (BMs) are becoming increasingly prevalent in modern applications. Estimating their production values involves various techniques, depending on the proportions of materials used. Among these techniques, artificial neural networks (ANN), fuzzy logic, statistical methods, and the adaptive neural fuzzy inference system are prominent. In this study, polyester biocomposites have been synthesized experimentally by adjusting the quantities of methyl ethyl ketone peroxide (MEKP), cobalt octoate (Co Oc) metal catalyst, marble factory waste, modified castor oil (MCO), and polyester raw material (UP) in specific ratios. The testing and analysis of these materials are conducted to determine parameters such as bulk density (BD), thermal conductivity coefficient (TCC), and activation energy (Ea). Subsequently, input and output values of the BMs are obtained, and ANN and adaptive neuro-fuzzy inference system (ANFIS) methods are employed for assessment. Both networks are trained and modeled using experimental data to construct their respective architectures. Validation of the models has been performed using data separate from the training set. A comparison between the actual values and those predicted by the network architectures revealed that the ANN method yielded outcomes with an average error of 0.3849 %, outperforming ANFIS. The findings showed that while ANFIS produced superior predictions for the Ea output value, the ANN structure fared better in predicting output values the BD and TCC.
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    Comparative Assessment of Lead (Pb) and Zinc (Zn) Leaching Behavior from Zinc Extraction Residues Using Monovalent and Divalent Chloride Salts
    (Springer, 2025) Turk, Feride N.; Ugur, Mucahit; Arslanoglu, Hasan
    It is crucial for waste management to economically utilize the solid leach residues released in zinc production facilities, classified as hazardous waste because of the metals they contain, without harming the environment and human health. Although the disposal of these residues often requires special technologies, hazardous wastes are left in the environment or landfills because of the expense of these technologies and the inadequacy of legal sanctions in some cases. Therefore, it is important from both an economic and environmental perspective to evaluate these residues and return them to the industry. This work aims to extract Pb and Zn metals from zinc extraction residuals in the presence of various chloride salts such as magnesium chloride, calcium chloride and potassium chloride. For this purpose, the chemical analysis of ZER (zinc extraction residual) was conducted by the LiBO2 fusion-HNO3 solubilization method, and its Pb and Zn contents were found to be 15.88% and 10.02%, respectively. The leaching experiments were carried out in two ways. The first group of leaching experiments was carried out by boiling under reflux and stirring, and KCl salt was found to be the most suitable leaching agent. The second group of experiments was performed in Erlenmeyer flasks using a shaker incubator at different temperatures (25-55 degrees C) and at varied KCl concentrations (0.6-5 N). Based on the experimental findings, the extraction efficiency of lead (Pb) is substantially higher than that of zinc (Zn) in the presence of all investigated chloride salts. While Pb dissolution demonstrates a strong dependence on the chloride salt concentration, particularly beyond certain threshold levels, the Zn extraction yield exhibits minimal variation across the same concentration range. This indicates that chloride ions preferentially promote the solubilization of Pb species, likely due to the formation of more stable and soluble Pb-Cl complexes, whereas Zn appears to have a lower affinity for chloride complexation under the studied leaching conditions. On the other hand, the Pb extraction value increased with increasing KCl concentration, and it reached 80.9% in KCl concentration of 4 N. In addition, the amount of Zn dissolved at different KCl concentrations plateaued at 25%.
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    Coordination-Driven Synthesis of Hierarchical Metal-Organic Network (MON) Particles for Efficient Cu(II) Removal: Structural Design-Characterization and Adsorption Performance
    (Springer Int Publ Ag, 2025) Turk, Feride N.; Arslanoglu, Hasan
    Copper (Cu(II)) contamination in aquatic systems is a pressing environmental issue due to its high toxicity, bioaccumulation potential, and adverse effects on ecosystems and human health. Developing adsorbent materials with high capacity, structural stability, and tunable surface chemistry is essential for efficient water purification. In this study, hierarchical metal-organic network (MON) particles were synthesized via a coordination-driven polycondensation of polyphenols and formaldehyde, resulting in robust, fiber-like structures with well-defined micro- (similar to 1.6 nm) and mesopores (similar to 13.9 nm) and a high surface area of 212.58 m(2)/g. The hierarchical pore architecture enhances mass transfer and adsorption kinetics, enabling a maximum Cu(II) adsorption capacity of 417.21 mg/g at 301.15 K, following the pseudo-second-order kinetic model and Langmuir isotherm. Thermodynamic analysis revealed that adsorption is spontaneous and endothermic, indicating strong chemisorption interactions through oxygen-containing functional groups. These results demonstrate that coordination-driven self-assembly represents an effective strategy for designing high-performance adsorbents with controlled pore structures and superior metal-binding capabilities. Beyond Cu(II) removal, this approach holds significant potential for developing next-generation materials for advanced water treatment, environmental remediation, and sustainable resource recovery.
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    Development of Polyurethane-Based Composites With Salt Clay and Industrial Wastes as Fillers: Corrosion, Mechanical Properties, and Machine Learning Insights
    (Wiley, 2025) Dag, Mustafa; Aydogmus, Ercan; Arslanoglu, Hasan; Yalcin, Zehra Gulten; Barlak, Semahat
    In this study, a polyurethane-based composite is developed by incorporating salt clay, ulexite, colemanite, and various other industrial waste materials. The effects of these fillers on the composite are evaluated and modeled using machine learning techniques. Among the tested models, random forest and neural network demonstrate the highest performance in predicting changes in compressive strength, hardness, and thermal conductivity. The dispersion of salt clay within the polyurethane matrix provides a 300%-500% increase in compressive strength and a 25%-40% improvement in hardness. Ulexite enhances compressive strength by 250%-350% and increases hardness by up to 30%, while colemanite contributes to a 400%-500% rise in compressive strength and a 35%-40% improvement in hardness. The addition of K & imath;rka clay waste and tincal further improves the composite's hardness and overall durability. Fly ash significantly increases compressive strength, although its effect on hardness is limited. The machine learning models effectively capture the relationship between input parameters and composite performance. The random forest model achieves a mean squared error (MSE) of 0.15 for compressive strength and 0.20 for hardness, while the neural network model yields the best results for thermal conductivity prediction with an MSE of 0.12. These findings highlight the potential of the developed composite for industrial applications, particularly in thermal insulation and low-load structural components. Future studies will focus on evaluating its performance under real-world conditions and further assessing its long-term durability.
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    Development of waste based biochar/lauryl alcohol as new shape-stable composite phase change material and its solar thermo-regulative performance in a building material
    (Elsevier, 2026) Timurkaynak, Erdogan; Sari, Ahmet; Nas, Memduh; Gencel, Osman; Ustaoglu, Abid; Arslanoglu, Hasan; Tyagi, V. V.
    The integration of phase change materials (PCMs) with biomass-derived biochar offers a sustainable and energy-efficient approach for developing composites with enhanced thermal functionality. In this study, a leakage-resistant composite was prepared by impregnating olive waste pulp (OWP)-based biochar (BC) with 45 wt% lauryl alcohol (LOH). The OWP-BC/LOH composite was incorporated into concrete by partially replacing sand at 10 %, 15 %, and 20 % to produce advanced materials for building energy conservation. Extensive tests covering morphological, physical, mechanical, thermal stability, thermal energy storage (TES), and solar thermoregulation were conducted. The compressive strengths of TES-integrated concretes were 45.31 MPa, 37.94 MPa, and 28.48 MPa for 10 %, 15 %, and 20 % replacements, respectively. While lower than the control, these values remain acceptable considering the improved thermal regulation. At 20 % replacement, apparent porosity, water absorption, and dry unit weight were measured as 23.3 %, 14.91 %, and 1869.11 kg/m3, respectively. FTIR analysis confirmed strong interactions between OWP-BC and LOH. DSC results revealed a melting point of 20.18 degrees C with a latent heat capacity of 111.9 J/g, maintaining stability after 600 heating-cooling cycles. TGA analysis indicated that the working temperature range was well below the onset of thermal degradation, ensuring long-term durability. Thermal conductivity decreased by 13 %, reaching 0.93 W/m & sdot;K. Furthermore, solar thermoregulation tests showed that 20 % OWP-BC/LOH concrete provided effective daytime cooling and nighttime heating. The use of OWP-BC/LOH composites could potentially reduce annual building energy consumption up to 27 kWh m-2 y-1 and lower CO2 emissions by
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    DTPA-Assisted Selective Leaching of Mo, Co, Ni, and Al from Spent Hydrodesulfurization Catalysts
    (Springer, 2025) Turk, Feride N.; Arslanoglu, Hasan
    The extraction of cobalt (Co), nickel (Ni), molybdenum (Mo), and aluminum (Al) from an alumina-supported hydrodesulfurization (HDS) spent catalyst was examined using diethylene triamine pentaacetic acid (DTPA) as a chelating agent. To assess the impact of different metals on leaching efficiency, a roasting pretreatment was performed on powdered catalyst samples at various temperatures (300-700 degrees C) and durations (15-360 min). The morphological and textural modifications before and after roasting were characterized using scanning electron microscopy (SEM) and Brunauer-Emmett-Teller (BET) analysis. The optimal roasting parameters were determined to be 600 degrees C for 180 min, under which the maximum metal extraction efficiencies were obtained: 71.05% for Mo, 80.06% for Co, 73.86% for Ni, and 15.33 % for Al. Leaching experiments were conducted with a particle size range of + 75 to - 30 mu m, a liquid-to-solid ratio of 15 mL/g, a DTPA concentration of 0.2 M, a leaching temperature of 60 degrees C, a duration of 180 min, and a stirring rate of 200 rpm. The findings highlight that both roasting temperature and time play a crucial role in enhancing metal dissolution from the spent catalyst.
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    Removal of Cr(VI) from Aqueous Solutions Using Thermal Power Plant Gas Purification Waste (Reduction and Adsorption of Hexavalent Chromium), Interpretation of Mechanism: Disposal of Waste and Residues
    (Springer Int Publ Ag, 2025) Saglam, Semanur; Eren, Sena; Turk, Feride N.; Arslanoglu, Hasan
    Flue Gas Desulfurization System (FGD) is a treatment system that has been made mandatory in thermal power plants for sulfur retention in recent years. FGD systems have been made mandatory in coal-based energy generating systems, especially in order to reduce the increasing greenhouse gas effect and to prevent the release of coal-derived sulfur oxides into nature. The hot waste steam from the boiler is sent to the FGD columns and milk of lime is fed to absorb the sulfur oxides. After treatment, thermal power plant gas treatment waste (PW) with a high content of gypsum is produced. In this study, the removal of chromium from aqueous solutions by PW was investigated. Cr(VI) adsorption studies were optimized using Taguchi analysis. In this context, L25 Taguchi orthogonal array was applied using 5 factors and 5 levels to optimize experimental parameters such as pH, dosage, contact time, concentration, temperature which affect adsorption. Elemental analysis, BET, TGA, XRD, XRD, FT-IR analyses were applied to determine the physicochemical properties of the waste. Adsorption isotherms and kinetics were also studied to investigate the Cr(VI) removal and mechanism of the material. The optimum experimental conditions were determined as initial pH 2.13, concentration 20 mg/L, dosage 22.5 g/L, time 12 h and temperature 32.5 degrees C by Taguchi method. Under these conditions, 100% Cr(VI) removal was successfully achieved. The results obtained show that PW is successful in Cr(VI) removal. The utilization of FGD waste is very important in terms of sustainability and environment. An alternative method has been presented as a solution to the increasing depletion of global water resources and the increasing need for land for PW storage.
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    Sustainable Epoxy Biocomposites Reinforced With Tenebrio molitor Biofiller: A Comprehensive Study on Thermal, Mechanical, and Dielectric Properties
    (Wiley, 2025) Ozgen, Inanc; Aydogmus, Ercan; Oner, Ilyas; Karagoz, Mustafa Hamdi; Arslanoglu, Hasan
    Obtaining biological material by drying and grinding Tenebrio molitor insects is original research in the field of innovative materials science. This study investigates the impact of T. molitor biofiller on the thermal, mechanical, and dielectric properties of epoxy-based biocomposites. The results revealed that increasing the content of the biofiller (from 0 to 4 wt.%) significantly reduced the bulk density (from 1134 to 1096 kg/m3), the Shore D hardness (from 77.6 to 73.1) and the thermal conductivity (from 0.112 to 0.090 W/mK), while enhancing the thermal insulation properties. A non-linear regression model confirmed the progressive reduction in density, with an optimal biofiller ratio of 2 wt.% minimizing trade-offs in thermal stability (activation energy: 178.37 kJ/mol). Dielectric constant measurements (4.09-3.78) showed improved insulating properties. Scanning electron microscopy (SEM) and other microscopic analyses confirmed homogeneous filler distribution and preserved structural integrity at optimal loadings. These findings highlight the potential of the biofiller-reinforced composites for use in lightweight, sustainable applications in the construction, electronics, and automotive industries, in line with the goal of innovating eco-friendly materials.
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    Valorization of biomass-derived magnetic activated carbon from vinasse and grape marc for sustainable bitumen modification
    (Pergamon-Elsevier Science Ltd, 2025) Ozdemir, Ahmet Munir; Yilmaz, Bahadir; Arslanoglu, Hasan
    Agricultural and food-processing residues represent abundant biomass resources with untapped potential for sustainable material production in the bioenergy sector. Functional renewable materials are obtained by using such residues in high-value applications such as bitumen modification. This study investigates the use of magnetic activated carbon (MAC), synthesized from by-products from bioethanol production (vinasse and grape marc) as a sustainable additive for modifying 160/220 penetration-grade bitumen. The objective is to enhance the rheological performance of bitumen under varying thermal and loading conditions. Modified binders containing 5 %, 10 %, and 15 % MAC were evaluated using dynamic mechanical analysis. Master curves for complex modulus and viscosity were developed using the Christensen-Anderson, Cross, and Carreau-Yasuda models. The results show that MAC incorporation improves elasticity, increases zero-shear viscosity, and enhances resistance to permanent deformation. In particular, it was observed that the addition of 15 % MAC increased the ZSV and G*/sin delta (64 degrees C) values by approximately 35 % and 95 % compared to pure binder, respectively. Rheological index (R) values increased by 38 %. The findings suggest that MAC-modified binders offer a promising solution for improving the performance of bituminous pavements in hot climates. Beyond advancing pavement performance, this work demonstrates a high-value utilization pathway for biomass residues, linking waste valorization to renewable material development within the bioenergy framework.
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    Valorization of Industrial Waste in Polymer Composites: Enhancing Mechanical and Thermal Properties for Insulation Applications Using Machine Learning Analysis
    (Wiley, 2026) Dag, Mustafa; Aydogmus, Ercan; Yalcin, Zehra Gulten; Arslanoglu, Hasan
    This study investigates the incorporation of industrial waste materials into polyurethane-based composites and evaluates their mechanical, thermal, and microstructural properties. The polyurethane matrix was synthesized from methylene diphenyl diisocyanate (MDI) and polyether polyol, into which various waste fillers, including ulexite, colemanite, tincal, and K & imath;rka clay, were introduced in different proportions. Mechanical testing revealed that specific wastes significantly enhance compressive strength, with ulexite- and clay-reinforced composites achieving improvements of 42.19% and 43.54%, respectively, compared to the pure polymer. The ulexite-clay composite exhibited the highest mechanical strength (38.67 kN), whereas tincal-containing samples demonstrated the weakest performance. Shore A hardness values generally decreased with waste incorporation, indicating that filler addition reduces polymer rigidity. Thermal conductivity results showed property variations within +/- 25%, where ulexite increased conductivity while K & imath;rka clay reduced it, thereby improving thermal insulation potential. Microstructural analysis using scanning electron microscopy (SEM) confirmed heterogeneous morphologies with dense filler distribution that intensified with increasing filler ratios. Fourier transform infrared spectroscopy (FTIR) indicated both physical and chemical interactions between the polymer matrix and boron-containing fillers, highlighting the complex interfacial bonding mechanisms. To complement the experimental analyses, machine learning (ML) models were applied to predict composite performance based on waste type and ratio. Among the tested algorithms, Random Forest (RF) demonstrated the highest predictive accuracy (R-2 > 0.90), confirming its suitability for modeling composite properties. The integration of ML provided quantitative insights into the role of individual and combined waste fillers, aligning closely with experimental observations. This research demonstrates that the controlled selection and optimization of waste fillers can enhance the performance of polyurethane composites, promote recycling of industrial byproducts, and support the development of sustainable materials for applications such as thermal insulation and structural components.