JOURNAL ARTICLE

Hydrometallurgical, pyrometallurgical and electrometallurgical extraction of niobium and tantalum: an overview.

  • Published In: Mineral Processing & Extractive Metallurgy, 2025, v. 134, n. 1. P. 3 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Haile, Michael Girma; Oladunni Oyelola, Alabi; Olufemi Aramide, Fatai; Ojo Seidu, Saliu; Akinlabi, Oyetunji 3 of 3

Abstract

This review paper focuses on the extraction processes of niobium and tantalum, detailing hydrometallurgical, pyrometallurgical, and electrometallurgical methods used to recover these metals from their ores. Hydrometallurgical techniques involve aqueous leaching, solvent extraction, and precipitation, offering high selectivity and lower environmental impact but requiring careful chemical management. Pyrometallurgical methods use high-temperature treatments such as calcination, roasting, and smelting, suitable for large-scale and fast processing but associated with high energy consumption and emissions. Electrometallurgical processes, including electrowinning and electrorefining, utilize electrolysis in aqueous or molten salt media to produce high-purity metals, though they demand significant energy and complex equipment. The paper also addresses environmental concerns linked to each method and highlights recent developments aimed at improving efficiency and sustainability, such as the use of ionic liquids, deep eutectic solvents, greener reagents, and advanced heating technologies.

Additional Information

  • Source:Mineral Processing & Extractive Metallurgy. 2025/03, Vol. 134, Issue 1, p3
  • Document Type:Article
  • Subject Area:Geology
  • Publication Date:2025
  • ISSN:2572-6641
  • DOI:10.1177/25726641241301982
  • Accession Number:183969098
  • Copyright Statement:Copyright of Mineral Processing & Extractive Metallurgy is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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