Synergistic enhancement of heavy rare earth elements leaching from ion-adsorption rare earth ores using fungal metabolites supplemented with ammonium sulfate

Variations in pore structures and permeabilities of ion adsorption rare earth ores during simulated in-situ leaching: Effect of newly formed clay particles and their swelling

Geology and geochemistry of China’s ion-adsorption rare earth ores are discussed. The structure and material constitution of Lognan, Huashan, Guposhan and Heling deposits are compared. The weathered layer structure, as well as the distribution, differentiation and occurrence forms of rare earth elements (REE) in the weathered layer are described. The prospecting indicators and criteria of readily dissociated adsorbed REE ore are identified to find this type ores in the territory of Russia. The weathered layer enclosing ion-adsorption rare earth ore features specific differentiation of REE. General composition of such ores is governed by the composition of the primary rare earth mineralization in mother granites. If granites contain much yttrium and heavy lanthanides, then ion-adsorption rare earth ore contain also much yttrium and heavy lanthanides. Regarding differentiation of REE, yttrium and heavy lanthanides mainly concentrate in the middle, most clayey part of the weathered layer, while cerium accumulates in subsurface lateritic soil. The prime feature of ion-adsorption rare earth ore is the prevalence of readily dissociated REE, which can reach a quantity of 80% and more but not less than a half. The rest REE concentrate in relict rock-forming minerals and accessories. The quantitative estimation of adsorption form of REE is necessary for the geological and economic appraisal of a deposit. It is assumed that the quantity of readily soluble REE should be not less than 0.05–50% of the total content. Russia has many regions with such geotectonic environment. It is required to explore ion-adsorption rare earth ore occurrences in these regions.

Study on the role of microbial metabolites in in-situ noncontact bioleaching of ion-adsorption rare earth ore

Column leaching of ion adsorption rare earth ore at low ammonium concentration

Recovery of rare earth from ion-adsorption rare earth ores with a compound lixiviant

Kaolinite (Kao) and montmorillonite (Mt) are the primary minerals present in ion-adsorption rare earth ores. Better understanding the adsorption/desorption characteristic for light and heavy rare earth elements (REEs) of Kao and Mt will be beneficial for the step-leaching and pre-enrichment of light and heavy REEs from ion-adsorption REE ores. The experiments show that the more negative ζ potential and the larger specific surface area of Mt contribute to the higher adsorption capacity of REEs. The stability of REEs onto Kao and Mt increases with the increase in adsorption pH. There are obvious differences in the desorption characteristic among Nd3+, Eu3+, and Lu3+ due to the different adsorption mechanisms. Lu3+ almost adsorbed on Kao through electrostatic force, and its recovery is 88% when the desorption pH was higher than 4; however, the recoveries were only 50% for Nd3+ and 56% for Eu3+, which interact with the Kao surface dominated by coordination bonds. However, the opposite desorption characteristic occurred on Mt. Based on these different desorption characteristics of light and heavy REEs, step-desorption and pre-enrichment for Nd3+ and Lu3+ from Kao and Mt were feasible. In the first lixivium of Kao, the percentage of Lu3+ is high, up to 68.4%, and Nd3+ is enriched in the second lixivium, with a percentage of 73.9%. As for Mt, Lu3+ is difficult to be desorbed and enriched in the second lixivium with a percentage of 87.7%.

Simulated bioleaching of ion-adsorption rare earth ore using metabolites of biosynthetic citrate: An alternative to cation exchange leaching

Heap leaching of ion adsorption rare earth ores and REEs recovery from leachate with lixiviant regeneration

The Shitouping region in Gannan is rich in rare earth resources and stands as one of the most significant ion adsorption type rare earth mineral resources, both in China and globally. This study utilizes Digital Elevation Model data to extract various geomorphological factors, including elevation, slope, aspect, curvature, and terrain roughness, and employs the Weights of Evidence method to analyze the favorable geomorphological conditions for ion-adsorption rare earth mineralization. The Support Vector Machine, Random Forest, and BP Neural Network models are used to predict the mineralization distribution of ion-adsorption rare earth ores in Shitouping, Jiangxi Province. The results indicate that topographical factors such as elevation, slope, and aspect play significant roles in the mineralization process. The elevation range of 464m - 711m and slope range of 0°-25.84° represent the most favorable conditions for mineralization. Terrain roughness and other topographic factors show a negative correlation with rare earth ore enrichment. Among the models used for mineralization prediction in the Shitouping ion-adsorption rare earth deposit, the Random Forest model performed the best, with an accuracy of 0.96 and an AUC of 0.95. The prediction results indicate that ion-adsorption rare earth ores are less prevalent in higher elevation areas. The predicted results, validated through comparison with field survey data, demonstrate high accuracy. This study integrates terrain data into the prediction of ion-adsorption rare earth ore mineralization, showcasing its potential for predicting mineralization distributions and providing crucial scientific support for the exploration and development of rare earth resources in the Shitouping region.

Interactive effects of ammonium sulfate and lead on alfalfa in rare earth tailings: Physiological responses and toxicity thresholds

Rare earth resource is a national strategic resource, which plays an essential role in the field of high technology research and development. In this paper, we aim to use remote sensing quantitative inversion prospecting technology, use surface-to-surface mode, and model inversion and evaluation through convolutional neural network model to achieve a new research method for large-scale, low-cost, rapid and efficient exploration of ion-adsorbed rare earth ore. The results show that the RE2O3 content of samples has significant negative correlation with the second, third and fourth band of GF-2 image, but has no significant correlation with the first band of GF-2 image; the convolution neural network model can be used to reconstruct the RE2O3 content. The content distribution map of RE2O3 obtained by inversion is similar to that of geochemical map, which indicates that the convolution neural network model can be used to invert the RE2O3 content in the sampling area. The quantitative inversion results show that the content distribution characteristics of ion adsorption rare earth ore in the study area are basically consistent with the actual situation; there are two main high anomaly areas in the study area. The high anomaly area I is a known mining area, and the high anomaly area II can be a prospective area of ion adsorption type rare earth deposit. It shows that the remote sensing quantitative inversion prospecting method of ion adsorption type rare earth deposit based on Convolutional Neural Networks (CNN) model is feasible.

Rare earth (RE) is an important strategic resource; however, there has been a growing concern about the environmental problems caused by RE mining, such as ammonia nitrogen pollution and heavy metal pollution. There is a limited research about the behavior of leaching agents and the fractionation of RE and heavy metal during the mining process for ion adsorption of rare earth ore (IRE-ore) in the previously available papers. In this study, (NH4)2SO4 solution, which commonly used in the production of mining IRE-ore, was used as a leaching agent. The adsorption behavior of ore soils on ammonium ions was explored by batch experiments. The adsorption process of IRE-ore on ammonium ions followed a pseudo-second-order equation and was controlled by the kinetics of surface adsorption and intra-particle diffusion; the ammonium ion adsorption isotherm conformed to the Freundlich isotherm equilibrium equation, and the higher concentration advantage made the ore soils possess a higher adsorption capacity of ammonium ion. In addition, the fractionation characteristics of lanthanum (La), cerium (Ce), and lead (Pb) in the ore soil during the leaching process were simulated based on the batch and column leaching experiments. The results demonstrated that the exchangeable states of La and Ce in IRE-ore were high, and the exchangeable, carbonate-bound La and Ce were almost all leached out by (NH4)2SO4 leaching agent, while the most of exchangeable Pb flowed out along with leaching agent, and a small amount of leached Pb in the ore soil was converted to iron and manganese oxide-bound Pb and enriched in the direction of migration of the leaching solution, and when the environment (e.g., pH and Eh) changed, this part of Pb may be re-activated. Our research might serve as crucial baseline knowledge for the adsorption of ammonium ions by ore soils, and provide a data reference for reducing the use of leaching agents and developing sustainable technologies for green mining of ion-adsorption RE ores.

Aluminum is a significant impurity in the ion-adsorption rare earth ore. The changes in the occurrences of aluminum have a great influence on the leaching of the rare earth ore. In this paper, the column leaching method was employed using magnesium sulfate as a leaching agent to investigate the effects of pH and magnesium sulfate concentration in the leaching agent on the leaching of aluminum and rare earths. The results show that at low magnesium sulfate concentrations, the leaching of rare earths is greatly enhanced, while the leaching of aluminum is not significantly affected by a decrease in the pH of leaching agent. At high magnesium sulfate concentrations, a slight increase in the leaching of rare earths is observed, accompanied by a significant increase in the leaching of aluminum upon decreasing the pH of the leaching agent. The leaching behavior of aluminum is related to the changes in the occurrences of aluminum during the leaching process. At low magnesium sulfate concentrations, low pH promotes the transition of Hy-Al to Sol-Al, but due to the low Mg2+ concentration in the leaching agent, Sol-Al is back-adsorbed onto the clays and transformed into Ex-Al, resulting in no significant increase in the aluminum content in the leach solution. However, at higher magnesium sulfate concentrations, aluminum in the leach solution comes mainly from the transformation of Ex-Al. Lowering the pH of the leaching agent can significantly promote the transition of Hy-Al to Sol-Al, thereby greatly increasing the aluminum content in the leach solution. The above results provide theoretical support for the optimization of the in situ leaching of ion-adsorption rare earth ore using magnesium sulfate.

Untargeted metabolomics reveals the mechanism for leaching rare earth elements from ion-adsorption rare earth ores using a composite lixiviant

Microbial community succession in response to in-situ coordinated leaching of ion-adsorption rare earth ores.