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Min, M.; Xu, H.; Chen, J.; Fayek, M. |
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Title |
Evidence of uranium biomineralization in sandstone-hosted roll-front uranium deposits, northwestern China |
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Year |
2005 |
Publication |
Ore Geology Reviews |
Abbreviated Journal |
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26 |
Issue |
3 |
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198-206 |
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Keywords |
Biomineralization, China, Roll-front uranium deposit, Sandstone |
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Abstract |
We show evidence that the primary uranium minerals, uraninite and coffinite, from high-grade ore samples (U3O8\textgreater0.3%) in the Wuyiyi, Wuyier, and Wuyisan sandstone-hosted roll-front uranium deposits, Xinjiang, northwestern China were biogenically precipitated and psuedomorphically replace fungi and bacteria. Uranium (VI), which was the sole electron acceptor, was likely to have been enzymically reduced. Post-mortem accumulation of uranium may have also occurred through physio-chemical interaction between uranium and negatively-charged cellular sites, and inorganic adsorption or precipitation reactions. These results suggest that microorganisms may have played a key role in formation of the sandstone- or roll-type uranium deposits, which are among the most economically significant uranium deposits in the world. |
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0169-1368 |
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THL @ christoph.kuells @ min_evidence_2005 |
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186 |
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Author |
Min, M.; Chen, J.; Wang, J.; Wei, G.; Fayek, M. |
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Title |
Mineral paragenesis and textures associated with sandstone-hosted roll-front uranium deposits, NW China |
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Journal Article |
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Year |
2005 |
Publication |
Ore Geology Reviews |
Abbreviated Journal |
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26 |
Issue |
1 |
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51-69 |
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Keywords |
China, Mineralogy, Paragenesis, Sandstone-hosted roll-type uranium deposit |
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Abstract |
We present a first paragenetic study of the Wuyier, Wuyisan, Wuyiyi and Shihongtan sandstone-hosted roll-front uranium deposits, northwest China. The mineralization is hosted by Lower–Middle Jurassic coarse- to medium-grained sandstones, which are dark-gray to black due to a mixture of ore minerals and carbonaceous debris. The sandstone is alluvial fan-braided river facies. Minerals associated with these deposits can be broadly categorized as detrital, authigenic, and ore-stage mineralization. Ore minerals consist of uraninite and coffinite. This is the first noted occurrence of coffinite in this type of deposit in China. Sulfide minerals associated with the uranium minerals are pyrite, marcasite, and less commonly, sphalerite and galena. The sulfide minerals are largely in textural equilibrium with the uranium minerals. However, these sulfide minerals occasionally appear to predate, as well as postdate, the uranium minerals. This implies that there are multiple generations of sulfides associated with these deposits. The ore minerals occur interstitially between fossilized wood cells in the sandstones as well as replace fossilized wood and biotite. The deposits are generally low-grade. Primary uranium minerals associated with the low-grade deposits are generally too small, ranging from 0.2 to 0.3 μm in diameter, to be observed by optical microscopy and are only observed by electron microscopy. Mineral paragenesis and textures indicate that these deposits formed under low temperature (30–50 °C) conditions. |
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0169-1368 |
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THL @ christoph.kuells @ min_mineral_2005 |
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175 |
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Milena-Pérez, A.; Piñero-García, F.; Benavente, J.; Expósito-Suárez, V.M.; Vacas-Arquero, P.; Ferro-García, M.A. |
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Title |
Uranium content and uranium isotopic disequilibria as a tool to identify hydrogeochemical processes |
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2021 |
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Journal of Environmental Radioactivity |
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227 |
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106503 |
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234U/238U, Betic cordillera, Groundwater, Hydrogeochemistry, Uranium natural isotopes |
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This paper studies the uranium content and uranium isotopic disequilibria as a tool to identify hydrogeochemical processes from 52 groundwater samples in the province of Granada (Betic Cordillera, southeastern Spain). According to the geological complexity of the zone, three groups of samples have been considered. In Group 1 (thermal waters; longest residence time), the average uranium content was 2.63 ± 0.16 μg/L, and 234U/238U activity ratios (AR) were the highest of all samples, averaging 1.92 ± 0.30. In Group 2 (mainly springs from carbonate aquifers; intermediate residence time), dissolved uranium presented an average value of 1.34 ± 0.13 μg/L, while AR average value was 1.38 ± 0.25. Group 3 comes from pumping wells in a highly anthropized alluvial aquifer. In this group, where the residence time of the groundwater is the shortest of the three, average uranium content was 5.28 ± 0.26 μg/L, and average AR is the lowest (1.17 ± 0.12). In addition, the high dissolved uranium value and the low AR brought to light the contribution of fertilizers (Group 3). In the three groups, 235U/238U activity ratios were similar to the natural value of 0.046. Therefore, 235U detected in the samples comes from natural sources. This study is completed with the determination of major ions and physicochemical parameters in the groundwater samples and the statistical analysis of the data by using the Principal Component Analysis. This calculation indicates the correlation between uranium isotopes and bicarbonate and nitrate anions. |
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0265-931x |
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THL @ christoph.kuells @ milena-perez_uranium_2021 |
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112 |
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Merembayev, T.; Yunussov, R.; Yedilkhan, A. |
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Title |
Machine Learning Algorithms for Stratigraphy Classification on Uranium Deposits |
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Journal Article |
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2019 |
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Procedia Computer Science |
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150 |
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46-52 |
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classification, geophysics logging data, machine learning, stratigraphy, uranium deposit |
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Machine learning today becomes more and more effective instrument to solve many particular problems, where there are difficulties to apply well known and described math model. In other words – it is a great tool to describe non-linear phenomena. We tried to use this technique to improve existing process of stratigraphy, and reduce costs on site by applying computer leaded predictions on the basis of existing on-field collected data. Article describes usage of machine learning algorithms for stratigraphy boundaries classification based on geophysics logging data for uranium deposit in Kazakhstan. Correct marking of stratigraphy from geophysics logging data is complex non-linear task. To solve this task we applied several algorithms of machine learning: random forest, logistic regression, gradient boosting, k nearest neighbour and XGBoost. |
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1877-0509 |
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THL @ christoph.kuells @ merembayev_machine_2019 |
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113 |
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Author |
Mekuria, W.; Tegegne, D. |
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Title |
Water harvesting |
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Book Chapter |
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Year |
2023 |
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Encyclopedia of Soils in the Environment (Second Edition) |
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593-607 |
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Climate change, Ecosystem services, Environmental benefits, Population growth, Resilient community, Resilient environment, Socio-economic benefits, Urbanizations, Water harvesting, Water quality, Water security |
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Water harvesting is the intentional collection and concentration of rainwater and runoff to offset irrigation demands. Secondary benefits include decreased flood and erosion risk. Water harvesting techniques include micro- and macro-catchment systems, floodwater harvesting, and rooftop and groundwater harvesting. The techniques vary with catchment type and size, and the method of water storage. Micro-catchment water harvesting, for example, requires the development of small structures and targets increased water delivery and storage to the root zone whereas macro-catchment systems collect runoff water from large areas. The sustainability of water harvesting techniques at the local level are usually constrained by several factors such as labor, construction costs, loss of productive land, and maintenance, suggesting that multiple solutions are required to sustain the benefits of water harvesting techniques. |
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Academic Press |
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Oxford |
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Goss, M.J.; Oliver, M. |
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978-0-323-95133-3 |
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THL @ christoph.kuells @ Mekuria2023593 |
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225 |
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