Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - WoS: 1Citation - Scopus: 1Predictive Modeling and SHAP-Based Interpretability of Manganese and Iron Dissolution in Multi-Acid Leaching Systems Using Hybrid Machine Learning(Multidisciplinary Digital Publishing Institute (MDPI), 2026) Top, Soner; Altiner, Mahmut; Kursunoglu, Sait; Kuzu, EmrahHydrometallurgical leaching processes contain complex and nonlinear parameter interactions that are difficult to capture with conventional empirical models. In this study, a multiple hybrid machine learning approach was developed to predict manganese (Mn) and iron (Fe) dissolution efficiency in leaching systems and performed using sulfuric acid (H2SO4), hydrochloric acid (HCl), and nitric acid (HNO3). A large-format dataset consisting of 204 independent leaching experiments was generated in which acid type, acid concentration (0.5-5 M), temperature (25-90 degrees C), solid/liquid ratio (100-200 g/L), leaching time (1-4 h), and eight different reducing agent types were systematically varied. XGBoost, LightGBM, CatBoost, and Random Forest algorithms were individually trained and subsequently combined with a Soft Voting Ensemble architecture. Hyperparameters were optimized using the RandomizedSearchCV method with 3-fold cross-validation. The XGBoost model achieved the highest prediction accuracy for Mn dissolution (R-2 = 0.8993, RMSE = 8.06%), while CatBoost demonstrated the best performance in Fe dissolution (R-2 = 0.8415, RMSE = 4.43%). SHAP analysis suggested that the dosage and type of reducing agents are the most influential predictive features for Mn dissolution, while acid molarity and temperature were identified as the dominant predictors for Fe leaching. Friedman test confirmed that performance differences among both Mn and Fe models were statistically significant (Mn: chi(2) = 32.76, p < 0.001; Fe: chi(2) = 25.96, p < 0.001). The developed models contribute significantly to hydrometallurgical process optimization by predicting the nonlinear effects of leaching parameters on metal dissolution with high accuracy. This study presents a comprehensive and interpretable machine learning framework supported by an extensive experimental dataset, a substantial portion of which has not been previously utilized or comparatively analyzed within a unified multi-acid framework, enabling systematic modeling of selective Mn-Fe dissolution across multiple acid systems and reducing agents.Article Citation - WoS: 3Citation - Scopus: 4Rare Earth Elements in the Global Economy: Usage, Recovery, and the Quest for Supply Security – A Review(Springer Heidelberg, 2026) Top, Soner; Ayten, Asim Mustafa; Altiner, Mahmut; Demir, Idris; Kursunoglu, SaitOften described as the vitamins of modern industry, rare earth elements (REEs) are indispensable for the deployment of low-carbon and clean energy technologies. However, ensuring a secure and sustainable REE supply remains a major challenge due to the strong interdependence between application-driven demand, extraction and processing technologies, and the geopolitical concentration of resources. This review adopts an integrated analytical framework in which these three dimensions are treated as interconnected components shaping the resilience of global REE supply chains. First, the major application sectors of REEs are examined to clarify how emerging energy and advanced manufacturing technologies drive demand for specific elements and amplify their strategic importance. Second, extraction and processing technologies are reviewed in relation to both primary and secondary resources, highlighting how technological maturity, process selection, and material characteristics constrain or enable supply expansion. Finally, geopolitical and strategic aspects of the REE supply chain are analyzed to demonstrate how resource concentration, policy instruments, and international dependencies directly influence technological deployment and industrial competitiveness. By explicitly linking application-driven demand, technological pathways for extraction and processing, and geopolitical supply structures within a unified framework, this review provides a coherent understanding of the systemic challenges facing the REE sector and identifies key leverage points for improving the robustness and sustainability of REE supply chains in the context of the global clean energy transition.Article Citation - WoS: 3Citation - Scopus: 3A Novel Biomass-Derived Reductant for Nitric Acid Dissolution of Manganiferous Iron Ore: Comparative Assessment of Organic Reductants(MDPI, 2025-12-31) Top, Soner; Altiner, Mahmut; Vapur, Huseyin; Kursunoglu, Sait; Stopic, SreckoThis study investigates the selective dissolution of manganese from a manganiferous iron ore using nitric acid (HNO3) in the presence of various organic reductants. A series of leaching experiments was performed to evaluate the effects of temperature, reductant type, and leaching time on Mn recovery, with particular emphasis on biomass (horse dung) and tartaric acid as novel reducing agents. The dissolution behaviour of Fe, Mn, Mg, Ca, and Al was systematically examined, revealing that Mn extraction was strongly enhanced in the presence of reductants, while Fe dissolution remained below 10% under all conditions. The maximum Mn dissolution exceeded 90% at 90 degrees C using biomass and reached nearly 85%-90% with tartaric acid at elevated temperatures. Kinetic studies were conducted by applying reaction order models and the shrinking core model. The results indicated that Mn dissolution in HNO3 medium is predominantly controlled by surface chemical reaction, with Arrhenius analysis yielding activation energies of 27.74 kJ/mol for biomass and 21.26 kJ/mol for tartaric acid. These relatively low values confirm the efficiency of organic reductants in facilitating Mn reduction and dissolution. To sum up, comparison of reductant efficiency revealed that, at the lowest concentrations, the dissolution of Mn followed the sequence glucose > sucrose > oxalic acid > tartaric acid > maleic acid > biomass > citric acid > acetic acid. At the highest concentrations, the trend shifted, with citric acid emerging as the most effective, followed by tartaric acid > oxalic acid > glucose > sucrose > maleic acid > biomass > acetic acid.Article Citation - WoS: 4Citation - Scopus: 5Recovery of Manganese From Spent Batteries Using Activated Carbon Powder as Reductant in Sulfuric Acid Solution(Asian Journal of Chemistry, 2013) Kursunoglu, Sait; Kaya, MuammerRecovery of manganese from spent batteries was investigated using activated carbon powder as a reducing agent in sulfuric acid solution. The effects of four different leaching parameters (sulfuric acid concentration, amount of activated carbon powder, temperature and time) on the leaching of manganese from spent batteries were investigated using central composite design technique. The maximum manganese recovery conditions were determined as 1 M of sulfuric acid concentration, 3 g of activated carbon powder, 80 degrees C of temperature and 3 h of leaching time. Under these conditions, the recovery of manganese was 86.39 % and pH value of the solution was 0.77. According to the reductive acid leaching results, an empirical second order equation for manganese recovery based on four investigated parameters was calculated. The observed values of manganese recoveries using model equation were found to be in a good agreement with the predicted values (R-2 = 0.92).Article Citation - WoS: 7Citation - Scopus: 5Beneficiation of Low-Grade Iron Ore Using a Dry-Roll Magnetic Separator and Its Modeling via Artificial Neural Network(Springer, 2025-02-24) Fariss, Abdourahman Hassan Brahim; Ibrahim, Ahmedaljaali Ibrahim Idrees; Ozdemir, Ali Can; Top, Soner; Kursunoglu, Sait; Altiner, MahmutThe beneficiation of low-grade iron ore (39.5% Fe-(T) grade) using a dry-roll magnetic separator was investigated. The ore was characterized using Mineral Liberation Analysis (MLA). It was determined that the ore was composed of iron oxide (goethite and hematite), quartz, chlorite, muscovite, plagioclase, and other minerals. The effect of particle size (PS, - 1 + 0.500 mm, - 0.500 + 0.300 mm, and - 0.300 + 0.125 mm), splitter position (SP, 43 degrees and 58 degrees), cleaning stage (CS, 1 and 2), conveyor speed (CoS, 3, 5, and 7 Hz), magnetic field strength (MFS, 0.2 T and 0.4 T) on the recovery of the magnetic product was investigated. Experimental results show that the product (- 1 + 0.500 mm) with the Fe-(T) grade of 67.67% can be obtained, but its recovery was not at an acceptable value (< 30%). Furthermore, the Fe-(T) grade of the product (- 0.500 + 0.300 and - 0.300 + 0.125 mm) could not reach satisfactory levels<bold>.</bold> The artificial neural network (ANN) method was conducted on the results of experimental studies. Three different training algorithms were employed for modeling, and their performance was assessed using statistical evaluation criteria. The results demonstrate that Bayesian Regularization (BR) algorithm exhibited better performance compared to others in predicting both Fe(T) grade and recovery rate during the testing phase. These findings support the notion that ANN algorithms can be a powerful modeling and prediction tool in the field of mineral processing.Article Citation - Scopus: 17Hydrometallurgical Processing of Nickel Laterites- A Brief Overview on the Use of Solvent Extraction and Nickel/Cobalt Project for the Separation and Purification of Nickel and Cobalt;(Chamber of Mining Engineers of Turkey, 2019-06-01) Kursunoglu, Sait; Kaya, MuammerIn this study, a brief overview of the solvent extraction (SX) application for the separation and purification of nickel and cobalt in hydrometallurgical processing of laterite nickel ores is presented. This paper consists of two parts: firstly, the SX of nickel and cobalt from sulphate leach solutions is described; and secondly, the development of hydrometallurgical plants for the processing of laterite nickel ores that involve solvent extraction technique is discussed. The most important extractants are shortly given in the first part of the study. It is seen that the extraction and separation of nickel and cobalt from the impure leach solution of laterite nickel ores can be performed by either using a single extractant system that is called as a direct solvent extraction (DSX) or a mixture of two or more extractant which is known as a synergistic solvent extraction system (SSX). Mixed sulphide precipitation (MSP) and mixed hydroxide precipitation (MHP) processes are mentioned. This paper is also addressed advantage and disadvantages of each extraction system. It is shown that capital investment expenditure, operational investment expenditure and mineralogical content are the most important factors that can affect the selection of the appropriate hydrometallurgical process for lateritic nickel ore. © 2023 Elsevier B.V., All rights reserved.Article Manganzı Demir Cevherinden Manganın Çözündürülmesinde Farklı İndirgeme Maddelerinin Etkisi(Chamber of Mining Engineers of Turkey, 2022-06-26) Top, S.; Altiner, Mahmut; Kursunoglu, SaitIIn this paper, the manganese extraction from a manganiferous iron ore was investigated using reductive leaching. Various chemicals were used as a reducing agent to leach manganese selectively from the ore in the presence of sulfuric acid (H2SO4) solution. Firstly, optimum dissolution values were determined for selective manganese dissolution without using a reducing agent. As it was aimed at the selective extraction of manganese from the ore, the reductive leaching tests were conducted by adding the reducing agents under the following optimal parameters: a leaching time of 1 h, a stirring speed of 300 rpm, a temperature of 70°C, a sulfuric acid concentration of 1 M where the ore was leached with an extraction ratio of 11.54% Mn and 2.16% Fe. Manganese was dissolved with high efficiencies (up to 97.46%) from the ore by using different organic compounds (tartaric acid (C<inf>4</inf>H<inf>6</inf>O<inf>6</inf>), oxalic acid (C<inf>2</inf>H<inf>2</inf>O<inf>4</inf>), citric acid (C<inf>6</inf>H<inf>8</inf>O<inf>7</inf>), glucose (C<inf>6</inf>H<inf>12</inf>O<inf>6</inf>), sucrose (C<inf>12</inf>H<inf>22</inf>O<inf>11</inf>), and maleic acid (C<inf>4</inf>H<inf>4</inf>O<inf>4</inf>)) as the reducing agents. © 2022 Elsevier B.V., All rights reserved.Article Citation - Scopus: 6Extraction of Lanthanum and Cerıum from a Bastnasite Ore By Direct Acidic Leaching(Chamber of Mining Engineers of Turkey, 2020-06-01) Kursunoglu, Sait; Top, S.; Hussaini, Shokrullah; Gokcen, H. S.; Altiner, Mahmut; Ozsarac, Safak; Kaya, MuammerThe extraction of lanthanum (La) and cerium (Ce) from a bastnasite ore by direct acidic leaching was investigated. The effects of acid concentration and leaching temperature on the extraction of La and Ce from the ore were tested. Using nitric (NHO3), more than 85% of the La and Ce were simultaneously extracted into leach solution whereas the La and Ce dissolutions were determined as less than 85% by using sulfuric acid (H2SO4). The La dissolution exceeded 90% by using hydrochloric acid (HCl); however, the Ce dissolution remained below 85% under the following conditions: solid-to-liquid ratio of 20% (w/v), the acid concentration of 20%, leaching temperature of 25°C and leaching time of 1 h. The result revealed that HNO3 could be used as a solvent for the maximum simultaneous extraction of the La and Ce from the bastnasite ore. The leaching temperature had no crucial effect on the dissolution of La and Ce when HNO3 or HCl solutions were preferred as a solvating agent. However, the leaching temperature had a slight positive effect on the dissolutions of La and Ce when H2SO4 was used as a solvent. © 2023 Elsevier B.V., All rights reserved.