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: 8Citation - Scopus: 8Separation of Mn and Fe From a Manganiferous Iron Ore Using Horse Dung as Reductant: A Zero Waste Approach(Springer, 2022-01-13) Top, Soner; Altiner, Mahmut; Kursunoglu, SaitThe separation of manganese and iron from a manganiferous iron ore using horse dung (biomass) as reductant was investigated in a sulfuric acid solution, and 99.80% Mn and 17.76% Fe were extracted into the solution under these leaching conditions: 1 M sulphuric acid concentration, 120 g/L biomass, 1/10 solid to liquid ratio, 300 rev/min stirring speed, 90 degrees C leaching temperature, and 3 h leaching time. In the first precipitation step, the iron and aluminum were first rejected from the solution at pH 5.04. Thereafter, 98.58% Mn was precipitated at pH 10 in the second step. The precipitate was identified as a pyrochroite mineral. After the leaching, the residue was subjected to a carbothermal reduction process conducted at 700 degrees C for 10 min in the presence of no extra reductant. The residue was converted to magnetite mineral, which can be easily recovered by magnetic separation. Based on the experimental results, a flowsheet has been proposed.Article Citation - WoS: 7Citation - Scopus: 7Recovery of Lithium From Spent Coin-Type Lithium Manganese Dioxide Cr Cells by Acidic Leaching in the Presence of Potassium Permanganate as Oxidant(Springer, 2022-09-20) Kursunoglu, Sait; Top, Soner; Altiner, Mahmut; Ozsarac, Safak; Kaya, MuammerThe selective leaching of lithium from spent coin-type lithium manganese dioxide CR cells by oxidative leaching and precipitation of Li2CO3 from Li-bearing leach solution has been experimentally and theoretically investigated. The oxidative leaching experiments were carried out using sulfuric acid in the presence of potassium permanganate (KMnO4). The dissolutions of lithium, manganese, nickel, and cobalt were found to be 84.8%, 0.9%, 46.6%, and 9.7%, respectively. The results demonstrated that a considerable amount of manganese and cobalt remained in the leach residue. The Li-bearing leach solution was fed to an impurity removal stage. It was observed that a substantial amount of lithium loss, along with manganese, nickel, and cobalt, was determined at pH 10. At standard temperature and pressure, the species of lithium as a function of pH, lithium concentration, and carbonate concentration was evaluated for the generation of Li2CO3 from the oxidative leach solution. The results revealed that the precipitation of lithium as lithium carbonate is thermodynamically feasible from the solution at high pHs.Article Citation - WoS: 23Citation - Scopus: 27Production of Alpha-Alumina from Black Aluminum Dross Using NaOh Leaching Followed by Calcination(Springer, 2020-07-27) Turk, Murat; Altiner, Mahmut; Top, Soner; Karaca, Serkan; Bouchekrit, ChafiaThe aim of this work is to produce alpha-alumina particles from aluminum (Al) dross via leaching-precipitation-calcination processes. In the leaching test, the effects of parameters such as the temperature, NaOH concentration, and time were investigated based on the Taguchi approach. In addition, the effect of the particle size on the Al extraction rate was determined. The Al extraction rate ranged from 78.64% to 93.11% and from 78.35% to 91.99% for ground dross and as-received dross, respectively. In the precipitation test, the pH of the leachate solution was decreased using HCl to remove Al ions as Al hydroxide precipitate. The precipitate was calcined at 1000 degrees C to 1200 degrees C for 270 min. The morphological and polymorphic properties of the products were characterized by scanning electron microscopy, atomic force microscopy, and x-ray diffraction analysis. The experimental findings indicated that the calcination temperature and stabilization time were critical for producing alpha-alumina particles rather than other polymorphs.Article Citation - WoS: 4Citation - Scopus: 5Characterization of Nickel in Chromite Beneficiation Tailings by Mineral Liberation Analysis and Its Recovery by H2SO4 Leaching Followed by Oxalic Acid Precipitation(Springer, 2023-11-13) Altiner, Mahmut; Ibrahim, Ahmedaljaali Ibrahim Idrees; Kursunoglu, Sait; Top, Soner; Bayat, OktayThis study investigated the recovery of nickel from tailings (0.2% Ni) obtained in a chromite beneficiation plant using H2SO4 leaching followed by oxalic acid precipitation. The tailings were characterized using mineral liberation analysis. Ni was found as Fe-Ni, Fe-Ni-Co sulfide minerals, which were encapsulated in serpentine, olivine, pyroxene and clinochlore. Liberated fine chromite minerals benefited from magnetic separation followed by Falcon concentrator. A chromite product with a grade > 37% was obtained. The effect of leaching conditions including acid concentration, temperature, time and solid-to-liquid ratio on the leaching behavior of Ni was investigated based on the Taguchi approach. It was possible to extract Ni with a rate of > 98% from the tailings using the following conditions: H2SO4 concentration of 3 M, solid-to-liquid ratio of 1:20 and ambient temperature for 2 h. Finally, Ni was precipitated as an oxalate form with a precipitation rate of 72%. It is believed that implementing additional purification methods like solvent extraction may be essential to obtain a high-purity nickel product from the leach solution of oxalate precipitate. Experimental results indicate that the tailings used in this study are a good alternative as Ni resource in the near future.