01. Araştırma Çıktıları | WoS | Scopus | TR-Dizin | PubMed

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Citation - WoS: 5
Citation - Scopus: 4
12th June 2017 Offshore Karaburun-Lesvos Island Earthquake Coseismic Deformation Analysis Using Continuous Gps and Seismological Data
(SCIENTIFIC TECHNICAL RESEARCH COUNCIL TURKEY-TUBITAK, 2021) Yıldız, Hasan; Çırmık, Ayça; Pamukçu, Oya; Özdağ, Özkan Cevdet; Gönenç, Tolga; Kahveci, Muzaffer
Understanding the tectonic mechanism generated by the earthquakes and faults is possible only if the preseismic, coseismic and postseismic crustal deformation related to the earthquakes is determined properly. By the analysis of continuous GPS (CGPS) coordinate time series, it is possible to estimate the crustal deformation. Besides, accelerometer records at strong motion stations (SMSs) may support the CGPS-based estimates. In this study, CGPS coordinate time series were analyzed in comparison with the accelerometer records for clarifying the coseismic deformation caused by the earthquake occurred in the surrounding of Lesvos fault located in the northern part of Karaburun within the active mechanism that controls the area where the earthquakes occurred during June 2017 on the offshore Karaburun. The activity of this fault continued throughout June 2017 until the time when the main shock (12th June 2017, M-W = 6.2) occurred. We analyzed CGPS coordinate time series of AYVL and CESM and DEUG stations to determine the coseismic deformation due to the offshore Karaburun-Lesvos Island earthquake using the empirical mode decomposition (EMD) method. Besides, the EMD method results were compared with the accelerometer records obtained from the SMSs close to the CGPS stations and CGPS-based results were found to be consistent with the accelerometer records. Additionally, the horizontal displacements were calculated by Coulomb 3.3 software using different focal plane solutions and compared with CGPS-based results. Consequently, it is suggested an integrated use of CGPS and strong motion accelerometer networks for the joint assessment of the crustal deformation and for the cost-effective use of existing observation networks as well as for the establishment of future observation networks at lower cost.
3D Printable Mortars with Green Materials: Sustainable Solutions with Nanocellulose
(Taylor & Francis Ltd, 2025) Turk, Ayse; Turk, Furkan; Edebali, Serpil; Keskin, Ulku Sultan
This study aims to improve the fresh and hardened properties of 3D-printable mortars. For this purpose, mortar mixtures containing cellulose nanofibres (CNF) obtained from the green algae of the Cladophora sp., which is abundant in lakes and causes environmental pollution if not recycled, as well as commercially available cellulose nanocrystals (CNC) and welan gum (WG) were prepared. The results showed that CNF was the most effective additive in improving fresh-state rheology, increasing yield stress by approximately 6 times and thixotropy by 48 times compared to the reference sample. Additionally, the CNF-modified mortar could carry a load of 50 N in the fresh state. The CNC additive showed the best mechanical performance, increasing compressive strength by 12%. Cellulosic additives were also observed to reduce shrinkage. Nanocellulose additives also increased the interlayer adhesion strength. All additives used have improved the properties of 3D-printable mortars. This study successfully produced a 3D-printable concrete/mortar additive from Cladophora sp., an environmentally detrimental waste material.
Academic Graph: a Literature Review System
(Institute of Electrical and Electronics Engineers Inc., 2022) Çataltaş, M.; Yumuşak, S.; Oztoprak, K.
As the number of academic publications increase, preparing a literature review becomes more challenging. This paper introduces an automated literature review support system to ease the literature review process for academia with reference graphs, abstract and full document summaries, paper clusters by keywords, abstracts, and abstract summaries combined. The output of the proposed system may ease exploring the state-of-the-art research. © 2022 IEEE.
Citation - WoS: 11
Citation - Scopus: 15
Accuracy Assessment of Dems Derived From Multiple Sar Data Using the Insar Technique
(SPRINGER HEIDELBERG, 2021) Karabörk, Hakan; Makineci, Hasan Bilgehan; Orhan, Osman; Karakuş, Pınar
In this study, digital elevation models (DEMs) derived from AlosPalsar data (Japanese Space Agency-JAXA), Sentinel-1A data, and Envisat ASAR data (European Space Agency-ESA) were compared by using a global navigation satellite system (GNSS). In addition, AW3D30, SRTM, and ASTER GDEM (open-access DEMs) data were also included in the accuracy evaluation. The DEM accuracies were investigated in three different terrain types, namely a plain area, mountainous area and agricultural area, and compared at elevation values on a pixel-based. The accuracy obtained from the ALOS PALSAR satellite data was found to be more reliable for all three terrain types. The standard deviation and root mean square values were calculated and compared to each other. The results of the accuracy assessments showed that the best result for the plain area was obtained with the Sentinel-1A and SRTM data, for the mountainous area was obtained with the SRTM data and for agricultural area was obtained with the ALOS PALSAR and SRTM data.
Citation - WoS: 1
Citation - Scopus: 1
An Accurate and Novel Numerical Simulation With Convergence Analysis for Nonlinear Partial Differential Equations of Burgers-Fisher Type Arising in Applied Sciences
(Walter De Gruyter Gmbh, 2022) Kürkçü, Ömür Kuvanc; Sezer, Mehmet
In this study, the second-order nonlinear partial differential equations of Burgers-Fisher type are considered under a unique formulation by introducing a novel highly accurate numerical method based on the Norlund rational polynomial and matrix-collocation computational system. The method aims to obtain a sustainable approach since it contains the rational structure of the Norlund polynomial. A unique computer program module, which involves very few routines, is constructed to discuss the precision and efficiency of the method and these few steps are described via an algorithm. A residual function is employed in both the error and convergence analyses with mean value theorem for double integrals. The considered equations in the numerical tests stand for model phenomena arising widely in applied sciences. Graphical and numerical comparisons provide a clear observation about the consistency of the method. All results prove that the method is highly accurate, eligible, and provides the ultimate operation for aforementioned problems.
Accurate Edge Detection With Support of Reflectance Transformation Imaging
(Institute of Electrical and Electronics Engineers Inc., 2022) Kaya, Burhan; Durdu, Akif
Reflectance Transformation Imaging (RTI) is a method of photographing an object that reveals details that are invisible to the naked eye. The input of RTI consists of a series of images captured by a fixed positioned camera and each illuminated from a known and different direction by lights. Reflection Transform Imaging is widely used to produce quality models from multi-light image data. It is frequently preferred for various studies in the field of cultural heritage. For the first time in this paper, the RTI photographing method has been used outside of its traditional using way. It is used to solve the well-known problem of edge detection. Reflection transform cannot be used actively, because it is difficult to create an RTI experimental environment in daily life. However, under certain conditions, the approaches mentioned in this paper will be used in daily life, from the analysis of images in every field. In this paper, the ideas that it can be applied in every partially controlled area that needs high resolution object detection are discussed. With the method mentioned in this statement, a new approach has been proposed and proven based on RTI basics for edge and corner detections. © 2022 IEEE.
Citation - WoS: 3
Citation - Scopus: 4
Achievable Rate Analysis for Two-Way Relay Non-Orthogonal Multiple Access Systems
(IEEE, 2021) Özdemir, Özgür
This paper investigates the performance of a non-orthogonal multiple access (NOMA) based two-way relaying system where the users want to exchange independent messages with the help of a decode-and-forward relay. We consider transmission over three phases where the first and second phases are allocated to the transmissions of the users and after detection the relay applies superposition coding and transmits the network encoded symbol to the users in the third phase. Exact analytical expressions are derived to characterize the achievable average rate of the system over independent Rayleigh fading channels. Computer simulations are also presented to confirm the theoretical analysis. Analytical and simulation results show that the proposed three-phase two-way relaying scheme with NOMA outperforms the two-phase and four-phase NOMA-based two-way relaying scenarios in terms of achievable average rate.
Citation - Scopus: 1
Achievable Rate of Noma-Based Cooperative Communication Systems With Best Relay Selection Over Cascaded Rayleigh Fading Channels
(IEEE, 2020) Özdemir, Özgür
In this paper, the achievable rate analysis of NOMA-based cooperative communication systems with best relay selection is studied. The cascaded Rayleigh fading channels are considered since investigations have shown that cascaded channel structure agree better with mobile network models such as inter-vehicular communication systems. A cooperative network where a source terminal communicates with a destination directly and through a selected relay among K relays is considered and the achievable average rate of this system using NOMA is found by computer simulations. The obtained results for cascaded Rayleigh fading channels in case of decode and forward protocol have shown that the average rate is decreased as the cascading degree increases. It has been also seen that for a given cascading degree the average rate performance of the system is increased when the number of total relays is increased.
Citation - Scopus: 5
Achieving Shojinka by Integrated Balancing of Multiple Straight Lines With Resource Dependent Task Times
(Springer New York LLC, 2019) Atasagun, Y.; Kara, Y.; Can Atasagun, Gözde
The concept of Shojinka, which is an important element of Just in Time production system, is attaining flexibility on the number of workers in a workshop due to demand variations. Even though Just in Time production system adopts U-shaped line layout, traditional straight lines can be combined and balanced in an integrated manner to obtain the advantages of Shojinka. In this case, the problem, which is called Integrated Balancing of Multiple Straight Lines, arises. On the other hand, the basic assumption of assembly line balancing is that every task’s time is fixed. However, in practice, different resource alternatives such as equipment or assistant worker may be available to process a task with different times. The problem in this case is to assign tasks and resources to stations that minimise total cost. In this study, a binary integer mathematical model is presented for integrated balancing of multiple straight lines, assuming that task times are resource dependent. The proposed model is illustrated and validated using several examples. An experimental analysis is also conducted to emphasize the advantages of the integrated balancing concept, compared to the situation in which the lines are balanced independent from each other. The experimental results show that, when multiple straight assembly lines are balanced in an integrated manner with resource dependent task times, an average total cost improvement of 23.105% can be obtained compared to the independent balances of the lines. This is a significant improvement that emphasizes the importance of balancing multiple straight lines in an integrated manner, to take the advantages of shojinka and to adhere to the main philosophy of Just in Time. © Springer Nature Switzerland AG 2019.
Citation - WoS: 12
Citation - Scopus: 17
Acoustic-Driven Airflow Flame Extinguishing System Design and Analysis of Capabilities of Low Frequency in Different Fuels
(Springer, 2022) Taşpınar, Yavuz Selim; Köklü, Murat; Altın, Mustafa
Traditional fire extinguishing methods can harm people and nature. For this purpose, in this study, no harmful acoustic-driven airflow fire extinguishing system was developed and experiments were carried out to extinguish gasoline, kerosene, thinner (synthetic thinner) liquid fuels and liquid petroleum gas (LPG) flames. 17,442 extinguishing experiments were conducted in 5 different flame sizes, 54 different frequencies and 10 cm to 190 cm distance range. The data obtained were analyzed using the polynomial regression method. For liquid fuels, the frequencies of 10 Hz to 50 Hz at a distance of 10 cm to 100 cm, 10 Hz to 32 Hz at a distance of 100 cm to 150 cm, and 10 Hz to 28 Hz at a distance of 150 cm to 180 cm are effective extinguishing ranges. LPG fuel, 10 Hz to 45 Hz at a distance of 10 cm to 140 cm, frequencies of 15 Hz to 30 Hz at a distance of 140 cm to 180 cm are effective extinguishing ranges. In addition, caused by the compression of the woofers membrane inside the collimator and the injected airflow at frequency of 30 Hz reduced the 12 cm diameter metal plate from 86.2 degrees C to 18.8 degrees C in 5 min, and the metal plate left to cool down from 80 degrees C to 21.7 degrees C in 10 min at a distance of 100 cm. The average Mean Square Error value obtained as a result of polynomial regression analysis is 0.9544, and the Root Mean Square Error value is 1.2020.
An Actuated Computational Method for Treating Parabolic Partial Delay Integro-Differential Equations Constrained by Infinite Boundary
(Springer Basel Ag, 2023) Kurkcu, Omur Kivanc
For the first time via this study, the ultimate effort is inclined to numerically solve one-dimensional parabolic partial integro-differential equations with spatial-temporal delays and infinite boundary using an efficient matrix-collocation method dependent upon the orthoexponential polynomials. The method clearly actuates a novel procedure converting the unknown differential and delay terms into their matrix expansions at the collocation points, and evaluating the integral part bounded by the half-line. The existence of the singular integral part is also validated by the orthoexponential polynomial solution. In addition to these novelties, an error bound estimation is developed via a boundary property of the orthoexponential polynomials. The resulting solutions are improved via the residual error analysis. Some numerical benchmark examples are included to indicate the accuracy and validity of the method, deploying graphical and numerical instruments. It can be noticeable to conclude that the proposed method achieves both drastic and useful approximation for highly stiff problems derived from the aforementioned equations.
Citation - WoS: 3
Citation - Scopus: 2
Adaptive Traffic Management Model for Signalised Intersections
(Kauno Technologijos Universitetas, 2024) Yalcinli, F.; Akdemir, B.; Durdu, A.
As population increases, one of the factors affecting life is traffic. Efficient traffic management has a direct positive impact on issues such as time, carbon dioxide emissions, and fuel consumption. Today, an important parameter under the heading of traffic is the signalling systems for intersections, which are operated with fixed-time, semi-actuated, fully actuated, and fully adaptive control methods. In this study, an adaptive traffic management model is developed for signalised intersections. The adaptive traffic management model developed includes phase extension with minimum and maximum time intervals dependent on density and phase skip features. Additionally, the most distinctive feature of the model is its flexible phase structure rather than a sequential phase. The Heybe intersection, located within the boundaries of Antalya province, is modelled one-to-one in the simulation of urban mobility (SUMO) simulation programme with real intersection data. The developed adaptive traffic management model is applied to the Heybe intersection, and the effects of the model are revealed. Improvements obtained from the SUMO simulation programme were verified through visual inspection, and high-accuracy results were determined. As a result of the studies, it was found that the application of the adaptive traffic management model developed at Heybe intersection, which has approximately 50,000 vehicles passing daily, resulted in a 27.2% improvement in the average delay per vehicle parameter, a 32.4% improvement in the average waiting time per vehicle parameter, and a 16.7 % improvement in the average speed per vehicle parameter. © 2024 Kauno Technologijos Universitetas. All rights reserved.
Addressing Time Delays in Blood Glucose Regulation for T1DM Using a PD Controller and Smith Predictor Method
(Institute of Electrical and Electronics Engineers Inc., 2025) Kurnaz, Ender; Aydogdu, Omer
Diabetes Mellitus, particularly Type 1 Diabetes (T1DM), is a condition where the pancreas does not produce enough insulin, causing abnormal Blood Glucose (BG) levels. Proper BG regulation is essential for managing T1DM and preventing related complications. In this research, a hybrid method that integrates the PD controller and Smith Predictor is employed to tackle the issue of time delays in blood glucose regulation for T1DM patients. This study compares two control strategies: a Proportional-Derivative (PD) controller and the Smith Predictor, both of which address time delays inherent in glucose monitoring and insulin delivery systems. The PD controller parameters are determined using MATLAB Simulink's PID Tuner, and the system's transfer function was derived through System Identification. The time response analysis of both control methods shows that while their rise times are similar, the Smith Predictor offers a significant reduction in delay and peak times. © 2025 Elsevier B.V., All rights reserved.
Citation - WoS: 3
Citation - Scopus: 3
Adjacent-Net: Deep Learning Classification of Adjacent Buildings for Assessing Pounding Effects Using Building Facade Images in Earthquake-Prone Regions
(Elsevier Science inc, 2025) Ekici, M. Yusa; Yavariabdi, Amir; Dogan, Gamze; Arslan, M. Hakan
In earthquake-prone areas, it is extremely important to carry out risk analyses of existing buildings and to take proactive measures in advance of potential earthquakes. Despite the availability of Rapid Seismic Assessment Methods (RSAMs), prioritising the seismic risk of buildings is a significant challenge due to the large number of residential buildings in the building stock. In RSAMs, many factors are taken into consideration to determine the earthquake risk priority. While specific construction conditions determine the risk parameters for the considered structures, one of them is the possible pounding effects (collision) of adjacent buildings. The fact that RSAMs have many evaluation parameters makes it difficult in site survey for technical experts to make decisions in some cases. Therefore, it is very important to perform these operations with software support. Based on this motivation, this study aims to perform pre-earthquake risk analysis of residential reinforced concrete buildings by assisting expert engineers (or facilitating the decision-making process in the absence of technical expertise) and to estimate the adjacent building parameter using building facade images for risk prioritisation. To achieve these objectives, a novel deep learning Convolutional Neural Network (CNN) model, named Adjacent-Net, is designed and developed to classify building facade images into adjacent or non-adjacent categories. The performance of Adjacent-Net is compared with various state-of-the-art CNN models such as DarkNet-53, EfficientNet, Inception ResNetV2, NasNet Large, ResNet-101, ShuffleNet, SqueezeNet, VGG-19, and Xception. For evaluation purposes, a dataset comprising 6170 building facade images is collected, and the results indicate that Adjacent-Net can accurately extract building adjacency parameters from images with an accuracy rate of approximately 98 %. This underscores the potential of intelligent systems in detecting collision scenarios, assessing the seismic risk of structures, and determining critical geometric parameters of buildings.
Citation - WoS: 2
Citation - Scopus: 2
Adrenal Lesion Classification With Abdomen Caps and the Effect of Roi Size
(Springer, 2023) Solak, Ahmet; Ceylan, Rahime; Bozkurt, Mustafa Alper; Cebeci, Hakan; Koplay, Mustafa
Accurate classification of adrenal lesions on magnetic resonance (MR) images are very important for diagnosis and treatment planning. The detection and classification of lesions in medical imaging heavily rely on several key factors, including the specialist's level of experience, work intensity, and fatigue of the clinician. These factors are critical determinants of the accuracy and effectiveness of the diagnostic process, which in turn has a direct impact on patient health outcomes. With the spread of artificial intelligence, the use of computer-aided diagnosis (CAD) systems in disease diagnosis has also increased. In this study, adrenal lesion classification was performed using deep learning on MR images. The data set used was obtained from the Department of Radiology, Faculty of Medicine, Selcuk University, and all adrenal lesions were identified and reviewed in consensus by two radiologists experienced with abdominal MR. Studies were carried out on two different data sets created by T1- and T2-weighted MR images. The data set consisted of 112 benign and 10 malignant lesions for each mode. Experiments were performed with regions of interest (ROIs) of different sizes to increase the working performance. Thus, the effect of the selected ROI size on the classification performance was assessed. In addition, instead of the convolutional neural network (CNN) models used in deep learning, a unique classification model structure called Abdomen Caps was proposed. When the data sets used in classification studies are manually separated for training, validation, and testing, different results are obtained with different data sets for each stage. To eliminate this imbalance, tenfold cross-validation was used in this study. The best results obtained were 0.982, 0.999, 0.969, 0.983, 0.998, and 0.964 for accuracy, precision, recall, F1-score, area under the curve (AUC) score, and kappa score, respectively.
Citation - WoS: 5
Citation - Scopus: 6
Adrenal Tumor Characterization on Magnetic Resonance Images
(WILEY, 2020) Barstuğan, Mücahid; Ceylan, Rahime; Asoğlu, Semih; Cebeci, Hakan; Koplay, Mustafa
Adrenal tumors occur on adrenal glands and are generally detected on abdominal area scans. Adrenal tumors, which are incidentally detected, release vital hormones. These types of tumors that can be malignant affect body metabolism. Both of benign and malign adrenal tumors can have a similar size, intensity, and shape, this situation may lead to wrong decision during diagnosis and characterization of tumors. Thus, biopsy is done to confirm diagnosis of tumor types. In this study, adrenal tumor characterization is handled by using magnetic resonance images. In this way, it is wanted that patient can be disentangled from one or more imaging modalities (some of them can includes X-ray) and biopsy. An adrenal tumor image set, which includes five types of adrenal tumors and has 112 benign tumors and 10 malign tumors, was used in this study. Two data sets were created from the adrenal tumor image set by manually/semiautomatically segmented adrenal tumors and feature sets of these data sets are constituted by different methods. Two-dimensional gray-level co-occurrence matrix (2D-GLCM), gray-level run-length matrix (GLRLM), and two-dimensional discrete wavelet transform (2D-DWT) methods were analyzed to reveal the most effective features on adrenal tumor characterization. Feature sets were classified in two ways: benign/malign (binary classification) and type characterization (multiclass classification). Support vector machine and artificial neural network classified feature sets. The best performance on benign/malign classification was obtained by the 2D-GLCM feature set. The best results were assessed with sensitivity, specificity, accuracy, precision, and F-score metrics and they were 99.17%, 90%, 98.4%, 99.17%, and 99.13%, respectively. The highest classification performance on type characterization was obtained by the 2D-DWT feature set as 59.62%, 96.17%, 93.19%, 54.69%, and 54.94% for sensitivity, specificity, accuracy, precision, and F-score metrics, respectively.
Adrenal Tumor Classification on T1 and T2-Weighted Abdominal Mr Images
(Institute of Electrical and Electronics Engineers Inc., 2019) Barstuğan, Mücahid; Ceylan, Rahime; Asoğlu, Semih; Cebeci, Hakan; Koplay, Mustafa
Adrenal tumors occur on adrenal glands and can be malignant. Adrenal glands consist of cortex and medulla. If cortex or medulla produce hormones extremely, the hormonal unbalance situation arises. This situation causes adrenal tumor occurrence on adrenal glands. In this study, adrenal tumors on T1 and T2-weighted MR images were classified by the SVM algorithm. Before the classification stage, different feature extraction algorithms and filtering methods were used for preprocessing. The classification results that were obtained by four different methods were evaluated on five different evaluation metrics as sensitivity, specificity, accuracy, precision, and F-score. The best classification performance was obtained with Method 2 on T1-weighted MR (Magnetic Resonance) images where the sensitivity, specificity, accuracy, precision, and F-score metrics were obtained as 99.17%, 90%, 98.4%, 99.17%, and 99.13%, respectively. © 2019 IEEE.
Citation - WoS: 9
Citation - Scopus: 11
Adrenal Tumor Segmentation Method for Mr Images
(ELSEVIER IRELAND LTD, 2018) Barstuğan, Mücahid; Ceylan, Rahime; Asoğlu, Semih; Cebeci, Hakan; Koplay, Mustafa
Background and objective: Adrenal tumors, which occur on adrenal glands, are incidentally determined. The liver, spleen, spinal cord, and kidney surround the adrenal glands. Therefore, tumors on the adrenal glands can be adherent to other organs. This is a problem in adrenal tumor segmentation. In addition, low contrast, non-standardized shape and size, homogeneity, and heterogeneity of the tumors are considered as problems in segmentation. Methods: This study proposes a computer-aided diagnosis (CAD) system to segment adrenal tumors by eliminating the above problems. The proposed hybrid method incorporates many image processing methods, which include active contour, adaptive thresholding, contrast limited adaptive histogram equalization (CLAHE), image erosion, and region growing. Results: The performance of the proposed method was assessed on 113 Magnetic Resonance (MR) images using seven metrics: sensitivity, specificity, accuracy, precision, Dice Coefficient, Jaccard Rate, and structural similarity index (SSIM). The proposed method eliminates some of the discussed problems with success rates of 74.84%, 99.99%, 99.84%, 93.49%, 82.09%, 71.24%, 99.48% for the metrics, respectively. Conclusions: This study presents a new method for adrenal tumor segmentation, and avoids some of the problems preventing accurate segmentation, especially for cyst-based tumors. (C) 2018 Elsevier B.V. All rights reserved.
Citation - WoS: 42
Citation - Scopus: 49
Adsorption of Malachite Green and Methyl Violet 2b by Halloysite Nanotube: Batch Adsorption Experiments and Box-Behnken Experimental Design
(Elsevier Ltd, 2022) Altun, Türkan; Ecevit, Hüseyin
Dyes constitute a significant part of the pollutants in industrial wastewater. In this study, halloysite nanotube (HNT) was used for adsorption of malachite green and methyl violet 2B dyes from the solution. Using batch adsorption experiments and response surface method, parameters affecting adsorption have been optimized. As a consequence of the batch experiments, after 60 min, the adsorption equilibrium state was achieved at 3 g L?1 HNT dosage, 125 mg L?1 dye concentration and natural solution pH. Temperature did not significantly affect the adsorption. The adsorption equilibrium data can be said to have fitted the Langmuir, Freundlich, Dubinin-Radushkevich and Temkin isotherms well for the both dyes. The Langmuir maximum monolayer malachite green and methyl violet 2B adsorption capacities (As) of HNT are 74.95 mg g?1 and 67.87 mg g?1, respectively. Adsorption processes are more consistent with the pseudo-second-order kinetic model. In addition, both intra-particle diffusion and film diffusion are effective as rate-determining steps in adsorption. Thermodynamic calculations showed that the adsorption is exothermic and spontaneous. The regeneration of HNT after adsorption was confirmed in five cycles. By using the Box-Behnken response surface method, the parameters affecting the adsorption process were modeled, the effects of these parameters on the adsorption efficiency were expressed mathematically and the optimum operating parameters were determined. © 2022
Citation - WoS: 30
Citation - Scopus: 32
Adsorptive Removal of Malachite Green Dye From Aqueous Solution by Ion Exchange Resins
(Springer Science and Business Media Deutschland GmbH, 2023) Yanardağ, D.; Edebali, S.
The adsorption of malachite green dye by commercially available synthetic polymers Diaion CR-11 and Amberlite IRC-748 resins has been studied. The effect of the initial dye concentrations, adsorbent dosage, contact time, pH, and temperature were examined. The dye adsorption mechanism for both resins was investigated using Langmuir, Freundlich, Scatchard, and Dubinin-Radushkevich (D-R) isotherm models. Also, experimental data were applied to the pseudo-first-order and pseudo-second-order kinetic models. The Langmuir isotherm and pseudo-second-order kinetic model best fit to the equilibrium data showed maximum adsorption capacities of 102.1 mg/g and 480.6 mg/g for Diaion CR-11 and Amberlite IRC-748, respectively. Thermodynamic studies show that the adsorption of malachite green dye increases with temperature and indicates that the adsorption process of both resins is endothermic. The negative value of change in Gibbs free energy shows spontaneous adsorption of malachite green on both resins. The polymer resins are characterized by Fourier transform infrared spectroscopy (FT-IR) and scanning electron microscope (SEM). © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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