Selective Extraction of Rare Earth Elements from Monazite Ores with High Iron Content
Autor: | Ruberlan Gomes Silva, Virginia S.T. Ciminelli, Leandro Augusto Viana Teixeira, D. Majuste, Angela Nair Avelar |
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Rok vydání: | 2019 |
Předmět: |
Rare-earth mineral
Magnesium Mechanical Engineering Metallurgy Extraction (chemistry) 0211 other engineering and technologies Metals and Alloys chemistry.chemical_element Thorium Sulfuric acid 02 engineering and technology General Chemistry Geotechnical Engineering and Engineering Geology chemistry.chemical_compound chemistry Control and Systems Engineering Aluminium Monazite Materials Chemistry 021102 mining & metallurgy Roasting |
Zdroj: | Mining, Metallurgy & Exploration. 36:235-244 |
ISSN: | 2524-3470 2524-3462 |
Popis: | Rare earth elements are essential for modern life products and green technologies. Recent supply constraints have boosted the development of rare earth projects after the price peak of 2011. The feasibility of a project depends on the definition of a processing route, which in turn depends primarily on the rare earth mineral, with monazite and bastnaesite representing the two most relevant minerals. Monazite-type ores usually contain high acid consumption impurities, such as iron, aluminum, calcium, magnesium, and phosphates, and may also contain prohibitive levels of radioactive thorium in its composition. This work presents a thermodynamic analysis of a monazite system and discusses the fundamentals of a selective process route for rare earth extraction from monazite ores with high iron content. This process involves sulfation by means of concentrated sulfuric acid and roasting at a high temperature. The route yields high rare earth extraction with low iron and thorium extractions and low acid consumption. Rare earth extractions as high as 80% were achieved, while iron and thorium extractions were lower than 1%, and acid consumption was lower than 0.34 kg of sulfuric acid per kg of ore. The operational window was compared to the one predicted by thermodynamic modeling, with 700 °C representing the optimal roasting temperature. |
Databáze: | OpenAIRE |
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