İlgi alanları

Sürdürülebilir Kalkınma Amaçları

• 3

• MakaleYalnız künye2026/r/gumushane/13554
  Comparison of Zn recovery prediction from carbonate ores with machine-learning methods

  Erkan, Ilker; Günen, Mehmet Akif

  This study addresses the challenge of predicting zinc (Zn) recovery from carbonate ores via sodium hydroxide (NaOH) leaching. This complex process influenced by variable ore composition, surface passivation effects, and nonlinear reaction dynamics, which complicate reagent optimization and process control in hydrometallurgical operations. To tackle this, a dataset containing 422 experimental observations was compiled from previous studies, incorporating ore composition and process parameters, such as NaOH concentration, leaching time, temperature, and solid-to-liquid ratio. Four regression models (decision tree, neural network, generalized additive model, and random forest) were trained and evaluated using performance metrics, such as coefficient of determination (R2), root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and symmetrical mean absolute percentage error (SMAPE). Among these, the random forest model achieved the best predictive accuracy, with R2 value of 0.8541 on the test set and the lowest error rates, demonstrating its effectiveness in capturing the complex relationships between input variables and Zn recovery. Explainable artificial intelligence, particularly SHapley additive exPlanations (SHAP) analysis, revealed that NaOH concentration, leaching time, and solid-to-liquid ratio had the most positive influence on Zn recovery, whereas elements such as Ca, Fe, and Pb had inhibitory effects. These findings align with known geochemical behavior and provide valuable insights for reagent optimization and process efficiency in leaching processes. This study demonstrates the practical potential of machine learning in mineral processing, offering a scalable framework for optimizing Zn recovery from non-sulfide ores and a data-driven approach to enhance decision-making in hydrometallurgical applications.

  • 
  İncele
• MakaleAçık Erişim2025/r/gumushane/11673
  Sulfur Removal From Low-Grade Turkish Kaolin Clay

  Erkan, Ilker; Alp, Ibrahim

  This study investigated the effects of NaOH direct leaching for sulfur removal from a kaolin ore from the Balıkesir region, Turkey. Characterization studies were undertaken before sulfur removal studies to enlighten the structure and originate the source of sulfur. The characterization studies revealed that the ore was mainly composed of quartz, with sulfur originating from alunite minerals with opal inclusions. The leaching process was tested under varying NaOH concentrations (1.5–2 M), temperatures (95 ± 2°C), and durations (2 h) in temperature-controlled closed systems to maintain consistency. Results demonstrated complete (100%) sulfur removal from alunite under optimal conditions. However, significant mass losses (18.15%–45%) occurred because of the dissolution of kaolinite along with alunite, indicating the method's effectiveness in sulfur removal but also its potential drawbacks for kaolinite retention.

  • 
  İncele
• MakaleAçık Erişim2024/r/gumushane/20134
  Exploring the utilization potential of kaolin in the Balıkesir Sındırgı region

  Alp, Ibrahim; Erkan, Ilker

  Natural kaolins may contain some metal cations (K+, Na+, Mg+2, Ca+2) and anions such as carbonate, phosphate, and sulfate as impurities, depending on the formation conditions. The kaolins of Turkiye generally give a high-quality white color after firing due to their low Fe2O3 content. Unfortunately, Turkiye’s kaolin deposits generally contain high levels of SO3. Since the alunite mineral, which is the source of SO3, cannot be removed from the structure by known methods, kaolins containing alunite can only be used in the white cement sector. In this study, the suitability of the kaolins of the Balıkesir Sındırgı region, which has a large part of the kaolin reserves of Turkiye, to the areas of use where kaolin is mostly used in its current state has been investigated, and the samples obtained from the region have been examined in which areas of use they are suitable for use in raw form, and suggestions have been made about the enrichment methods to be carried out by comparing with the studies in the literature.

  İncele
• MakaleAçık Erişim2024/r/gumushane/14136
  Central composite design modelling and developing a method for removing sulphate from an alunitic kaolin ore

  Erkan, İlker; Inal, Serkan; Alp, İbrahim

  The main mineral in kaolin ore, kaolinite, is well-known for its many uses in the paint, paper, and ceramics industries. The necessity of getting pure kaolinite is discussed in this work, with an emphasis on the extraction of impurities from kaolin. Specifically, alunitic kaolin, which is common in northwest Turkey, has sulfur concentrations higher than 3 % SO3, which means that it can't be used for many industrial purposes. Leaching is a popular method for removing sulfur, especially when done directly and through pre-treatment techniques like roasting. High-temperature roasting, however, presents difficulties since it causes phase transformation on kaolinite to metakaolin and mullite and on alunite to alum. The temperature of phase transformation is important on high temperature studies which affects negatively the thixotropic qualities that are essential for the production of ceramics. This study introduces a novel approach by optimizing roasting conditions and employing a central composite design methodology for leaching. The optimal parameters for the roasting studies were determined to be 525 °C for 3 h. For leaching, the ideal conditions were identified using the leaching recovery equation, which specifies 0.195 M NaOH, 80 °C, 127 min, and a 2.55 % solid content. These characteristics were confirmed by follow-up experiments, which showed a change in SO42− concentration from 3.03 % to 2.97 %, along with some structural changes in the roasted sample. The subsequent leaching process resulted in a significant drop in SO42− concentration to 0.46 %. By highlighting the effectiveness of lower-temperature roasting and optimizing experimental methodology, this research presents a novel thermochemical method for sulfur removal in alunitic kaolin.

  • 
  İncele
• MakaleAçık Erişim2023/r/gumushane/11921
  Investigation of geometric object and indoor mapping capacity of Apple iPhone 12 Pro LiDAR

  Günen, Mehmet Akif; Erkan, İlker; Aliyazıcıoğlu, Şener; Kumaş, Cavit

  LiDAR (light detection and ranging) sensors use laser beams to calculate distances in the surroundings. These sensors can be applied to a wide range of tasks, and they are frequently helpful in tasks like building 3D maps, navigating airplanes, robots, conducting mining operations, and automated driving. High-resolution distance measurements are taken by LiDAR sensors, but they also gather environmental data. This information aids in locating, identifying, and quantifying things and their surroundings. The iPhone 12 Pro, which Apple released in 2020, was evaluated for accuracy with various geometric shapes and its capacity to recognize indoor environments. Free of charge 3D Scanner and the Clirio Scan application were employed in this situation. However, it was found that the root mean square error and mean error in indoor mapping were ±1.41 cm and-0.56 cm in 3D Scanner and ±3.94 cm and-0.60 cm in the Clirio Scan application, respectively, despite the findings obtained showing low accuracy in scanning small geometric objects due to the scanning difficulty. Clirio does not reject the null hypothesis in the t-test that was conducted. The accuracy of the LiDAR sensor in indoor mapping has been shown to be more promising than that of small items. In order to evaluate the reliability and reusability of the indoor mapping application according to reference measurements, intraclass correlation test was performed and the results were determined to be reliable.

  İncele
• MakaleAçık Erişim2019/r/gumushane/11852
  Determination of the wear performance of diamond saw blades using inductively coupled plasma

  Inal, Serkan; Erkan, Ilker; Aydiner, Kerim

  Saw blades are one of the most used cutting tools. They compose the expensive parts of a cutting machine. Therefore, saw-blade wear is an important parameter governing the economy of the cutting process. Significant savings could be made when it is controlled effectively. In this study, a new methodology is employed for the determination of the saw-blade wear in the cutting of two types of marble. Wear of segments is determined by high-precision inductively coupled plasma method. Two types of marbles were used to investigate the wear performance of diamond-impregnated segments of circular saw-blade matrix. Taguchi mixed design L16 (43 21) is used as an experimental design and the results are evaluated statistically with Minitab. The results reveal that the specific wear rate (SWR) of Beige marble increases with the increase of the peripheral speed, traverse speed, depth of cut and down-cut mode operation. Additionally, it is demonstrated that the traverse speed and peripheral speed are the dominant cutting parameters affecting the SWR. It is also seen that similar trends are observed for Onyx marble (excluding peripheral speed). Finally, it is concluded that the proposed models can be effectively used for the estimation of the SWR.

  İncele