Chemical Composition and Petrogenetic Implications of Eudialyte-Group Mineral in the Peralkaline Lovozero Complex, Kola Peninsula, Russia

Kogarko, L. N.; Nielsen, Thorkild

doi:10.3390/min10111036

Cited by 15 publications

(5 citation statements)

References 26 publications

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“…The Lovozero peralkaline massif is a layered laccolith-like intrusion with an area of 650 km 2 . It intruded into the Archean granite-gneisses [29] (Figure 1a) and was emplaced at 370 ± 7 Ma by Rb-Sr dating [30].…”

Section: Geological Settingmentioning

confidence: 99%

“…Therefore, EGMs may be considered as geochemical indicators of magmatic crystallization conditions. EGMs may experience secondary transformation due to the ion-exchange processes according to various substitution schemes [2][3][4][5][6]. The possibility of post-crystallization changes results in a wide range of chemical compositions [7] and different space groups [8], which gave rise to the 31 mineral species according to the International Mineralogical Association (IMA) list of approved minerals [9].…”

Section: Introductionmentioning

confidence: 99%

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Zr-Rich Eudialyte from the Lovozero Peralkaline Massif, Kola Peninsula, Russia

et al. 2021

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The Lovozero peralkaline massif (Kola Peninsula, Russia) has several deposits of Zr, Nb, Ta and rare earth elements (REE) associated with eudialyte-group minerals (EGM). Eudialyte from the Alluaiv Mt. often forms zonal grains with central parts enriched in Zr (more than 3 apfu) and marginal zones enriched in REEs. The detailed study of the chemical composition (294 microprobe analyses) of EGMs from the drill cores of the Mt. Alluaiv-Mt. Kedykvyrpakhk deposits reveal more than 70% Zr-enriched samples. Single-crystal X-ray diffraction (XRD) was performed separately for the Zr-rich (4.17 Zr apfu) core and the REE-rich (0.54 REE apfu) marginal zone. It was found that extra Zr incorporates into the octahedral M1A site, where it replaces Ca, leading to the symmetry lowering from R3¯m to R32. We demonstrated that the incorporation of extra Zr into EGMs makes the calculation of the eudialyte formula on the basis of Si + Al + Zr + Ti + Hf + Nb + Ta + W = 29 apfu inappropriate.

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Section: Geological Settingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Zr-Rich Eudialyte from the Lovozero Peralkaline Massif, Kola Peninsula, Russia

et al. 2021

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“…Loparite-(Ce), ideally (Na,Ce,Sr)(Ce,Th)(Ti,Nb) 2 O 6 , is a ubiquitous accessory mineral of alkaline igneous rocks, including nepheline syenites and foidolites [1,2]. This mineral also occurs in carbonatites [3,4] and in contact with metamorphic and metasomatic rocks.…”

Section: Introductionmentioning

confidence: 99%

“…Currently, loparite ores are mined at the Karnasurt and Kedykvyrpakhk mines, located in the northwest of the massif. The study of the morphology and chemical composition of loparite-(Ce), as well as the genesis of loparite ores of the Lovozero massif, is the subject of many works [1,2,[10][11][12]. The researchers suggested early magmatic or late magmatic [1,12], or hydrothermal origins [11,13,14] for loparite-(Ce).…”

Section: Introductionmentioning

confidence: 99%

Polymineralic Inclusions in Loparite-(Ce) from the Lovozero Alkaline Massif (Kola Peninsula, Russia): Hydrothermal Association in Miniature

et al. 2023

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Polymineralic inclusions in loparite-(Ce) in alkaline rocks from the Lovozero massif (Russia) were investigated using electron microprobe analysis, Raman spectroscopy, and X-ray diffraction. A total of 21 mineral species and two groups of minerals (pyrochlore- and labuntsovite-group minerals) were found in these inclusions. Minerals in loparite-hosted inclusions can be divided into two groups: (1) minerals found typically in rocks bearing loparite-(Ce) grains (groundmass minerals) such as aegirine, magnesio-arfvedsonite, potassic feldspar, albite, fluorapatite, etc.; and (2) minerals that were not found in the rock outside of the loparite-(Ce) grains. The latter include lorenzenite, labuntsovite-group minerals, minerals of the neptunite–manganoneptunite series, vinogradovite, catapleiite, fluorite, britholite-(Ce), barylite, genthelvite, and barite, found in the studied samples exclusively inside loparite-(Ce) crystals. The minerals of the second group are typical hydrothermal minerals. We assume that the skeletal crystals of loparite-(Ce), when growing, captured both co-crystallizing minerals and small drops of the mineral-forming solution. Such drops subsequently crystallized within the loparite-(Ce), resulting in the formation of a hydrothermal mineral association.

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“…The next phase, (phase II), which accounts for about 77 percent of the total volume, consists of layered nepheline syenites with varied mineralogy and locally accessory loparite or eudialyte. Loparite is concentrated up to 25 percent, by volume, in some layers (Kogarko et. al., 2002).…”

Section: Alkaline To Peralkaline Granites and Syenitesmentioning

confidence: 99%

Modelling of liberation in Ta- and W-rich minerals

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With the general trend across all commodities towards the treatment of lower grade and medium grade ores, it is becoming increasingly important to develop the proper design for comprehensive mineralogical characterization and a complete procedure based on image analysis and grade distribution is proposed for the measurement of the liberation in the particles to reach the mineral liberation modeling. This thesis aims to develop an appropriate methodology to characterize complex low-grade Ta and medium grade W ores for the purpose of developing the most appropriate physical separation strategy. As result of this investigation a methodology is proposed for the mineralogical characterization and it consists of three different levels of characterization using different analytical techniques. Level 1, the simplest (which included chemical analysis, XRD, optical microscopy, SEM, and EMPA), was applied to Penouta and Mittersill ores and successfully characterized the mineralogy. Level 2, which included mineral characterization of the processed ores, and were XRD, SEM, and EMPA were needed for ores. The ores required the added sophistication of Level 3. In addition to the techniques of Level 1 and Level 2, Level 3 included the use of chemical analysis and automated SEM to estimate the mineralogical attributes of the ores. The insights from the mineralogical characterization were then used to inform the physical separation testing that was undertaken, for example, selective or bulk concentration. These results, together with the mineralogical characterization, indicated that selective gravity separation would be an appropriate processing route for this ore. The fine-grained Ta minerals required a P80 of about 100 µm. The final flow sheet produced a rougher concentrate that contained 103 ppm of Ta, at a recovery of 52%. In the Mittersill ore, the majority of the scheelite (>99%) was contained in hornblende, which itself represented approximately 33% of the ore. A bulk separation strategy using shaking table and the introduction of grinding to generate a P80 of 150 µm, was necessary to recover scheelite minerals to achieve a rougher concentrate of 2260 ppm W at a recovery of 87%. The mineralogical characterization of Mittersill, during which an association was found between scheelite and quartz, accounting for more than 17% of quartz in this ore with most of the remainder occurring as fine-grained quartz helped to guide the mineralogical characterization. This work describes a method for determining the downstream milling energy requirements for the mill products based on a Bond mill test performance. The grade distribution of particles at a given size fraction was calculated using a predictive liberation model. The recovery of particles in size/grade classes, image analysis using mineral liberation analysis (MLA), and function calculations were implemented for the modeling of the liberation. By describing the size, grade, and recovery data of particles in size/grade classes, a technique for the measurement of distribution functions was developed that relates beta distribution, a model for the function based on the incomplete beta function, and a solution to produce liberation modeling. It was shown that the predicted results agreed well with the observed results. The model was implemented in MATLAB, a simulation model, with King’s solution to the beta distribution function model that includes the liberation distribution Como indica la tendencia general en todos los productos hacia el tratamiento de minerales de leyes baja y media, se está volviendo cada vez más importante desarrollar diseños adecuados para una caracterización mineralógica integral. En este caso se propone un procedimiento completo basado en el análisis de imágenes y la distribución de leyess para la medición de liberación en las partículas, con el objetivo de alcanzar el modelo de liberación mineral. El objetivo de esta tesis es desarrollar una metodología adecuada para caracterizar los minerales complejos de Ta de baja y mediana ley con el fin de desarrollar estrategias de separación física más adecuada. Como resultado de esta investigación, se propone una metodología para la caracterización mineralógica y consta de tres niveles diferentes utilizando diferentes técnicas analíticas. El nivel 1, el más simple (que incluye análisis químicos, DRX, microscopía óptica, SEM y EMPA), se ha aplicado a los minerales de Penouta y Mittersill y se ha caracterizado correctamente la mineralogía. El nivel 2, que incluye la caracterización mineral del material ya procesado (entre ellos XRD, SEM y EMPA). Pa un mayor detalle de los minerales existentes, se requerían un nivel mas sofisticado de caracterización. Además de las técnicas del Nivel 1 y Nivel 2, el Nivel 3 incluía el uso de análisis químicos y SEM automatizado para estimar los atributos mineralógicos. Todos los datos obtenidos por la caracterización mineralógica fueron utilizados para supervisar las pruebas de separación física que se llevaron a cabo, por ejemplo, si se trata de una concentración selectiva o una concentración total. Estos resultados, junto con la caracterización mineralógica, indicaron que la separación por gravedad selectiva sería una ruta de procesamiento apropiada para este mineral. Los minerales Ta de grano fino requirieron un P80 de aproximadamente 100 µm. El diagrama de flujo final produjo un concentrado que contenía 103 ppm de Ta, a una recuperación del 52%. En el mineral de Mittersill, la mayoría de la scheelita (> 99%) estaba contenida en hornblende, que a su vez representaba aproximadamente el 33% del mineral. Fue necesaria una estrategia de separación a granel usando la mesa de sacudidas y la introducción de la molienda para generar un P80 de 150 µm, en la recuperación de minerales de scheelita para lograr un concentrado de 2260 ppm W con una recuperación del 87%. La caracterización mineralógica de Mittersill, durante la cual se encontró una asociación entre el scheelita y el cuarzo, representando más del 17% del cuarzo en este mineral, y la mayor parte del resto se produjo cuando el cuarzo de grano fino ayudó a guiar la caracterización mineralógica. Este trabajo describe un método para determinar los requisitos de energía de molienda aguas abajo para los productos de fábrica basados ¿¿en el rendimiento de la prueba de molturabilidad de Bond. La distribución en la leyes de las partículas en una fracción de tamaño dada se calculó usando un modelo de liberación predictivo. La recuperación de partículas por clases de tamaño / ley, fue desorrollado por medio de un MLA (Mineral liberatio analysis), desarrollando una técnica adaptando los datos del la miscroscopía con las funciones estadistica de ditribución beta. Los resultados coincidían con la modelización y se han obtenido los parametros de la distribución beta para los minerales de tantalio y tungsteno.

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Chemical Composition and Petrogenetic Implications of Eudialyte-Group Mineral in the Peralkaline Lovozero Complex, Kola Peninsula, Russia

Cited by 15 publications

References 26 publications

Zr-Rich Eudialyte from the Lovozero Peralkaline Massif, Kola Peninsula, Russia

Zr-Rich Eudialyte from the Lovozero Peralkaline Massif, Kola Peninsula, Russia

Polymineralic Inclusions in Loparite-(Ce) from the Lovozero Alkaline Massif (Kola Peninsula, Russia): Hydrothermal Association in Miniature

Modelling of liberation in Ta- and W-rich minerals

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