Solubility of the Pyrochlore Supergroup of Minerals in Supercritical Aqueous Fluoride Solutions

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

A review of experimental data on the solubility of niobium and tantalum oxides and oxyfluorides in fluoride solutions is performed. Using experimental data on the solubility of pyrochlore (CaNa)Nb2O6F and microlite (CaNa)Ta2O6F the thermodynamic properties of these minerals for 300–800°С have been calculated. Thermodynamic properties of albite, andalusite, muscovite, paragonite, and pyrophyllite for the temperature range 300–550°С have been clarified. Thermodynamic calculations modeling the influence of solution composition and mineral aluminosilicate associations on the solubility of pyrochlore and microlite in the supercritical region of physicochemical parameters have been carried out. Calculations show that the solubility of the considered ore minerals is very low and the removal of niobium and tantalum by metamorphosed solutions is not possible. The mechanisms of HF accumulation are proposed, which may play an important role in niobium and tantalum dissolution, recrystallization and replacement of ore mineral phases at limited distances.

About the authors

A. F. Redkin

Korzhinskii Institute of Experimental Mineralogy, Russian Academy of Sciences

Author for correspondence.
Email: redkin@iem.ac.ru
Chernogolovka, Moscow Region, Russia

N. P. Kotova

Korzhinskii Institute of Experimental Mineralogy, Russian Academy of Sciences

Email: redkin@iem.ac.ru
Chernogolovka, Moscow Region, Russia

Yu. B. Shapovalov

Korzhinskii Institute of Experimental Mineralogy, Russian Academy of Sciences

Email: redkin@iem.ac.ru
Chernogolovka, Moscow Region, Russia

N. N. Akinfiev

Institute of Geology of Ore Deposits, Petrography, Mineralogy, and Geochemistry, Russian Academy of Sciences

Email: redkin@iem.ac.ru
Moscow, Russia

References

Supplementary files

Supplementary Files
Action
1. JATS XML

Copyright (c) 2025 Russian Academy of Sciences

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).