Search Results (87)

Tin slags generated during cassiterite smelting in Brazil contain significant amounts of technologically important metals such as niobium, tantalum, and zirconium. Improper disposal of these materials represents both an environmental concern and the loss of a valuable secondary source of critical elements. This study aimed to characterize a Brazilian tin slag sample to evaluate its composition, morphology, and potential for metal recovery. The material was homogenized and analyzed by laser diffraction (particle size), ICP-OES (chemical composition), X-ray diffraction (mineral phases), differential scanning calorimetry (metallic tin), and scanning electron microscopy with energy-dispersive spectroscopy (morphology). The slag exhibited a heterogeneous particle size distribution (D90 = 0.75 mm, D50 = 0.30 mm, D10 = 0.09 mm) and a complex multiphase structure composed mainly of silica, calcium silicate, and zirconia. The chemical analysis revealed 4.8 wt% Nb and 0.8 wt% Ta, along with high concentrations of Zr (11.1 wt%), confirming the material’s potential as a secondary resource. Thorium (2.7 wt%) and uranium (0.3 wt%) were also detected, indicating the presence of radioactive constituents. The detailed characterization of the slag provides essential insights into its chemical and mineralogical complexity, which directly influence the selection of suitable recovery routes. Understanding the distribution of Nb- and Ta-bearing phases within the refractory silicate–zirconia matrix is fundamental for defining pretreatment and leaching strategies. Therefore, this study establishes a necessary foundation for the design of efficient hydrometallurgical processes aimed at recovering critical metals from Brazilian tin slags. Full article

This study introduces the Normalized Difference Gamma Ray Index (NDGRI), a novel spectral composite derived from Sentinel 2 imagery for mapping elevated natural gamma radiation in semi-arid and arid basins. We hypothesized that water-sensitive spectral indices correlate with gamma-ray hotspots in arid regions of Mongolia, where natural radionuclide distribution is influenced by hydrological processes. Leveraging historical car-borne gamma spectrometry data collected in 2008 across the Sainshand and Zuunbayan uranium project areas, we evaluated twelve spectral bands and five established moisture-sensitive indices against radiation heatmaps in Naarst and Zuunbayan. Using Pearson and Spearman correlations alongside two percentile-based overlap metrics, indices were weighted to yield a composite performance score. The best performing indices (MI—Moisture Index and NDSII_1—Normalized Difference Snow and Ice Index) guided the derivation of ten new ND constructs incorporating SWIR bands (B11, B12) and visible bands (B4, B8A). The top performer, NDGRI = (B4 − B12)/(B4 + B12) achieved a precision of 62.8% for detecting high gamma-radiation areas and outperformed benchmarks of other indices. We established climatological screening criteria to ensure NDGRI reliability. Validation at two independent sites (Erdene, Khuvsgul) using 2008 airborne gamma ray heatmaps yielded 76.41% and 85.55% spatial overlap accuracy, respectively. Our results demonstrate that NDGRI effectively delineates gamma radiation hotspots where moisture-controlled spectral contrasts prevail. The index’s stringent acquisition constraints, however, limit the temporal availability of usable scenes. NDGRI offers a rapid, cost-effective remote sensing tool to prioritize ground surveys in uranium prospective basins and may be adapted for other radiometric applications in semi-arid and arid regions. Full article

Rare earth elements (REEs) have significant application value in the quality control of nuclear materials and in traceability research in nuclear forensics. Methods were developed for the determination of REEs in uranium-bearing nuclear materials. The digestion parameters for uranium oxides and uranium ores, such as the digestion acid, digestion temperature, and digestion time, were optimized and reported. The optimized digestion parameters for uranium oxides were 2 mL HNO₃ at 160 °C for 3 h, and those for uranium ores were 7 mL mixed acid (HNO₃–HClO₄–HF = 5:5:3) at 180 °C for 36 h. Two digestion methods were demonstrated to be effective for the quantitative recovery of REEs. The suitable system and specifications for different resin columns were investigated to achieve a high decontamination factor of U (10⁵) by UTEVA resin. The corresponding loading system was 10 mL 4 M HNO₃, and the elution system was 6 mL 4 M HNO₃. Additionally, the analysis of ultra-trace REEs in high-uranium matrices was accomplished using two UTEVA resins. The developed methods were subjected to the Cochran test and the Grubbs test, and the relative standard deviation (RSD) for all REEs was below 6%. In uranium oxide samples with different spiked amounts, the recovery of REEs exceeded 80% in all cases, and the RSDs were all less than 10%. The method’s detection limits were below 10 ppt for all REEs (except for Ce), ensuring the accurate measurement of REEs in uranium-bearing nuclear materials. Full article

With nuclear power playing an increasing role in efforts to reduce carbon emissions, the development of effective and sensitive monitoring tools for (radio)toxic elements in the environment has become essential. This review highlights recent advances in fluorescent probes developed for the detection of key elements associated with the nuclear industry, including uranium, cesium, strontium, technetium, zirconium, and beryllium. Various sensor platforms, ranging from organic ligands and DNAzymes to metal–organic frameworks and quantum dots, offer promising features, such as high sensitivity, selectivity, and suitability for environmental matrices. Several recent designs now achieve detection limits in the nanomolar to picomolar range, revealing new perspectives for environmental and biological applications. Full article

This study investigates the biochemical and elemental composition of the test of Diadema setosum (D. setosum), a sea urchin species increasingly processed in Turkey, where the shell is commonly treated as industrial waste. Specimens were collected from the Mediterranean and Aegean Seas, and the test material was subjected to amino acid profiling, protein quantification, and X-ray fluorescence (XRF) analysis. The results revealed a considerable protein content (8.03%) and a rich amino acid spectrum dominated by glycine, aspartic acid, and arginine, supporting the presence of residual structural proteins even after processing. Mineral analysis showed a high calcium oxide concentration (43.19%), alongside significant levels of magnesium, phosphorus, strontium, and trace elements such as zinc, copper, and molybdenum. Rare earth elements and radionuclides including neodymium, samarium, and uranium were also detected, suggesting sediment interaction. These findings suggest that D. setosum tests could represent a sustainable source of bioavailable minerals and proteinaceous material, with prospective applications in fish or livestock feed, hydroxyapatite synthesis, or calcium oxide production, pending further validation. Full article

Background/Objectives: This study aimed to evaluate the effects of lung injury induced by insoluble uranium oxide particles on gut microbiota and related metabolites in rats. Methods: The rats were randomly divided into six UO₂ dose groups. A rat lung injury model was established through UO₂ aerosol. The levels of uranium in lung tissues were detected by ICP-MS. The expression levels of the inflammatory factors and fibrosis indexes were measured by enzyme-linked immunosorbent assay. Paraffin embedding-based hematoxylin & eosin staining for the lung tissue was performed to observe the histopathological imaging features. Metagenomic sequencing technology and HM700-targeted metabolomics were conducted in lung tissues. Results: Uranium levels in the lung tissues increased with dose increase. The expression levels of Tumor Necrosis Factor-α (TNF-α), Interleukin-1β (IL-1β), Collagen I, and Hydroxyproline (Hyp) in rat lung homogenate increased with dose increase. Inflammatory cell infiltration and the deposition of extracellular matrix were observed in rat lung tissue post-exposure. Compared to the control group, the ratio of Firmicutes and Bacteroides in the gut microbiota decreased, the relative abundance of Akkermansia_mucinphila decreased, and the relative abundance of Bacteroides increased. The important differential metabolites mainly include αlpha-linolenic acid, gamma-linolenic acid, 2-Hydroxybutyric acid, Beta-Alanine, Maleic acid, Hyocholic acid, L-Lysine, L-Methionine, L-Leucine, which were mainly concentrated in unsaturated fatty acid biosynthesis, propionic acid metabolism, aminoacyl-tRNA biosynthesis, phenylalanine metabolism, and other pathways in the UO₂ group compared to the control group. Conclusions: These findings suggest that uranium-induced lung injury can cause the disturbance of gut microbiota and its metabolites in rats, and these changes are mainly caused by Akkermansia_mucinphila and Bacteroides, focusing on unsaturated fatty acid biosynthesis and the propionic acid metabolism pathway. Full article

The rapid neutron-capture process (r-process) is responsible for the creation of roughly half of the elements heavier than iron, including precious metals like silver, gold, and platinum, as well as radioactive elements such as thorium and uranium. Despite its importance, the nature of the astrophysical sites where the r-process occurs, and the detailed mechanisms of its formation, remain elusive. The key to resolving these mysteries lies in the study of chemical signatures preserved in ancient, metal-poor stars. These stars, which formed in the early Universe, retain the chemical fingerprints of early nucleosynthetic events and offer a unique opportunity to trace the origins of r-process elements in the early Galaxy. In this review, we explore the state-of-the-art understanding of r-process nucleosynthesis, focusing on the sites, progenitors, and formation mechanisms. We discuss the role of potential astrophysical sites such as neutron star mergers, core-collapse supernovae, magneto-rotational supernovae, and collapsars, that can play a key role in producing the heavy elements. We also highlight the importance of studying these signatures through high-resolution spectroscopic surveys, stellar archaeology, and multi-messenger astronomy. Recent advancements, such as the gravitational wave event GW170817 and detection of the r-process in the ejecta of its associated kilonovae, have established neutron star mergers as one of the confirmed sites. However, questions remain regarding whether they are the only sites that could have contributed in early epochs or if additional sources are needed to explain the signatures of r-process found in the oldest stars. Additionally, there are strong indications pointing towards additional sources of r-process-rich nuclei in the context of Galactic evolutionary timescales. These are several of the outstanding questions that led to the formation of collaborative efforts such as the R-Process Alliance, which aims to consolidate observational data, modeling techniques, and theoretical frameworks to derive better constraints on deciphering the astrophysical sites and timescales of r-process enrichment in the Galaxy. This review summarizes what has been learned so far, the challenges that remain, and the exciting prospects for future discoveries. The increasing synergy between observational facilities, computational models, and large-scale surveys is poised to transform our understanding of r-process nucleosynthesis in the coming years. Full article

To provide safe drinking water in contaminated hydrogeological environments, it is essential to have precise geochemical information on contamination hotspots. In this study, Geographic Information System (GIS) and multivariate statistics were utilized to analyze the spatial patterns, occurrence, and major factors controlling uranium (U) concentrations in groundwater. The global and local Moran’s I indices were utilized to detect hotspots and cool spots of U distribution. The substantial positive global Moran’s I index (at a p-value of 0.05) revealed a geographical pattern in U occurrences. The spatial clusters displayed patterns of drinking water source with U concentrations below and above the WHO limit, categorized as “regional U cool spots” and “regional U hotspots”, respectively. Spatial autocorrelation plots revealed that the high–high potential spatial patterns for U were situated in the northeastern region of the study area. As the order of queen’s contiguity increased, prospective low–high spatial patterns transitioned from the Faridkot district to the Muktsar district for U. Further, the multivariate statistical analysis methods such as correlation and principal component analysis (PCA) plots revealed substantial positive associations (p-value < 0.05) between U and total dissolved solids (TDS), salinity (SL), bicarbonate (HCO₃⁻), and sodium (Na) in groundwater from both shallow and deeper depth, indicating that these water quality parameters can significantly influence the occurrence of U in the groundwater. The output of the random forest model shows that among the groundwater parameters, TDS is the most influential variable for enrichment of U in groundwater, followed by HCO₃⁻, Na, F⁻, SO₄²⁻, Mg, Cl⁻, pH, NO₃⁻, and K concentrations. Additionally, the results of health risk assessment indicate that 47.86% and 41.3% of samples pose risks to children and adults, respectively, due to F⁻−contamination. About 93.49% and 89.14% of samples pose a risk to children and adults, respectively, due to U contamination, whereas 51.08% and 39.13% of samples pose a risk to children and adults, respectively, from NO₃⁻ contamination. The current data indicates an urgent need to create cost-effective and efficient remediation techniques for groundwater contamination in this region. Full article

To achieve a significant breakthrough in the exploration of uranium resources in the Guangzitian area of northern Guangxi, China, an innovative combination of exploration methods was implemented at the peripheral regions of the Guangzitian uranium deposit under the guidance of the following principle: “exploring the edges and identifying the bottom, delving deep and un-covering blind spots”. This study introduces geo-electrochemical integrated technology for prospecting research at the peripheral areas of the Guangzitian deposit. By validating the technology’s effectiveness on known geological sections, distinct geo-electrochemical extraction anomalies were identified above recognized ore bodies. Simultaneously, soil ionic conductivity and thermally released mercury anomalies were observed, partially indicating the presence of concealed uranium deposits and fault structures. These findings demonstrate that geo-electrochemical integrated technology is effective in detecting buried uranium mineralization in this region. Subsequently, a geological-geoelectrical prospecting model was established through a systematic analysis of anomaly characteristics and metallogenic regularity, and it was subsequently applied to unexplored areas. As a result, one key anomaly verification zone, one Class A comprehensive anomaly zone, two Class B comprehensive anomaly zones, and one Class C comprehensive anomaly zone were identified within the unexplored research area. Drilling engineering validation was conducted in the No. Ι key anomaly verification zone, resulting in the discovery of an industrial-grade uranium ore body. This achievement not only provides critical technical support but also develops a robust theoretical foundation for future mineral exploration endeavors. Full article

Lava rises, locally known as stony rises, are Pliocene–Holocene volcanic landforms occurring throughout the Victorian Volcanic Plain (VVP) in Victoria, Australia. Stony rises are not only important to understanding the geological history of Victoria but are culturally significant to Aboriginal Australians and have ecological importance. Currently, the mapping of stony rises is manually performed at a case study level rather than a landscape level. Remote sensing technologies such as LiDAR data, satellite imagery, and aerial imagery allow for the mapping of stony rises from an aerial perspective. This paper aims to map stony rises using remotely sensed and geophysical data at a landscape level on a younger lava flow (~42,000 years old) within the Victorian Volcanic Plain (the Warrion Hill and Red Rock Volcanic Complex) by utilizing an object based random forest machine learning approach. The results show that stony rises were successfully identified in the landscape to an accuracy of 78.9%, with 2716 potential new stony rises identified. Out of 34 predictor variables, we found the most important variables to be slope gradient, local elevation, DEM of Difference (change in height), Normalized Difference Water Index (NDWI), Clay Mineral Ratio, the concentration of radiometric elements (Potassium, Thorium, and Uranium), Total Magnetic Intensity, and Ecological Vegetation Class (EVC). The results from this study highlight the ability to detect a volcanic landform at a landscape scale using an ensemble of predictor variables that include topographic, spectral information and geophysical data. This lays the foundation towards a uniform approach for mapping stony rises throughout the VVP and similar landforms (such as tumuli) worldwide. Full article

In the late 1960s, a uranium province was explored in the Shu-Sarysu depression in southern Kazakhstan. These mining operations can lead to potential contamination of the environment and pose health risks to the population. The aim of this study is to carry out environmental monitoring in uranium deposits and assess indoor radon levels in settlements located in the uranium mining area in the southern region of Kazakhstan. Elevated outdoor ambient equivalent dose rates (0.5–1.2 µSv/h) were detected beyond the buffer zone, particularly near a preserved self-flowing well, where the highest activity concentrations of natural radionuclides were recorded (²²⁶Ra—2350 Bq/kg, ²³²Th—270 Bq/kg, ⁴⁰K—860 Bq/kg), exceeding background levels. Indoor ambient equivalent dose rates in the settlements of Taukent, Zhuantobe, Tasty, and Shu ranged from 0.04 to 0.15 μSv/h, while outdoor levels varied from 0.03 to 0.1 μSv/h, remaining within global and regional average values. Radon concentrations were highest in Tasty and Shu but did not exceed the permissible level. However, Shu exhibited the highest radiation exposure dose (>4 mSv/y), approaching the lower range of recommended action levels (3–10 mSv/y). These findings highlight the necessity for continuous monitoring and potential mitigation strategies in areas with naturally elevated radiation levels. Full article

Uranium plays an important role in the modern nuclear industry. However, such a radioactive element can also cause severe damage to the environment once leaked or discharged into water or air, having a huge impact on the safety of the biosphere. In this work, we pioneered the use of fluorescent monomers as imprinted units, which promoted fluorescence emission of the material. A novel porous aromatic framework was obtained with uranyl ion chelating sites, namely MIPAF-15. The unique N-O chelating pockets on the 4-bromo-1-H-indole-7-carboxylic acid gave rise to high coordination affinity toward uranyl ions, which enabled the fast adsorption rate of uranyl ions and a uranyl ion adsorption capacity of 44.88 mg·g⁻¹ at 298 K with an initial pH value of 6.0 and the uranyl concentration of 10 ppm. At the same time, the fluorescence quenching effect of MIPAF-15 was observed upon its adsorption of uranyl ions, which allowed the selective detection of uranyl ions with a detection limit of 5.04 × 10⁻⁸ M, lower than the maximum concentration of uranyl ions in drinking water specified by the World Health Organization (6.30 × 10⁻⁸ M) and United States Environmental Protection Agency (1.11 × 10⁻⁷ M). This kind of multifunctional porous material produces a favorable pathway for the detection, removal and degeneration of highly pollutive ions, promoting the overall sustainable development of the natural environment. Full article

Remote detection of radioactive materials in mixtures using handheld or portal detectors remains a challenge because of factors such as low concentration, environmental interference, sensor noise, and other complications. This work introduces a fast framework for generating realistic mixture spectra. Moreover, we present mixture isotope identification using data generated by the fast framework. Researchers have examined a range of conventional and recent algorithms within the fields of machine learning and deep learning. An application to uranium enrichment-level prediction has been included. Extensive simulation experiments validated the efficacy of the proposed framework. Full article

Growing awareness of the environmental cost of mining operations has led to increased research on monitoring and restoring legacy mine sites. Hyperspectral imaging (HSI) has emerged as a valuable tool in the mining life cycle, including post-mining environment. By detecting variations in crystal structure and physicochemical attributes on the surface of materials, HSI provides insights into site environmental and ecological conditions. Here, we explore the capabilities of drone-based HSI for mapping surface patterns related to contamination dispersal in a legacy uranium-rare earth element mine site. Hyperspectral data across the visible to near-infrared (VNIR) and short-wave infrared (SWIR) wavelength ranges (400–2500 nm) were collected over selected areas of the former Mary Kathleen mine site in Queensland, Australia. Analyses were performed using data-driven (Spectral Angle Mapper—SAM) and knowledge-based (Band Ratios—BRs) spectral processing techniques. SAM identifies contamination patterns and differentiates mineral compositions within visually similar areas. However, its accuracy is limited when mapping specific minerals, as most endmembers represent mineral groups or mixtures. BR highlights reactive surfaces and clay mixtures, reinforcing key patterns identified by SAM. The results indicate that drone-based HSI can capture and distinguish complex surface trends, demonstrating the technology’s potential to enhance the assessment and monitoring of environmental conditions at a mine site. Full article

This research investigates the elemental composition of 78 drinking water samples collected during the summer, autumn, and winter of 2023 in different districts of Almaty city. Seasonal average concentrations and standard deviations were calculated for a range of chemical elements, including arsenic (As), beryllium (Be), cobalt (Co), cadmium (Cd), copper (Cu), lithium (Li), molybdenum (Mo), nickel (Ni), lead (Pb), selenium (Se), uranium (U), mercury (Hg), aluminum (Al), barium (Ba), chromium (Cr), iron (Fe), manganese (Mn), strontium (Sr), vanadium (V), zinc (Zn), calcium (Ca), potassium (K), magnesium (Mg), and sodium (Na), across three distinct datasets. The sites of sampling represent various categories of drinking water sources. The quality of drinking water was assessed by comparing the obtained data with current national, international, and World Health Organization (WHO) standards. Drinking water contaminant indices for the heavy metal groups were calculated and the water quality compliance with the hygienic criteria adopted in the Republic of Kazakhstan was determined. With the exception of two sampling points, the levels of non-carcinogenic risk remained below the acceptable threshold. The predominant pathway for exposure for both adults and children was identified as the oral ingestion of hazardous elements. Carcinogenic risks linked to Ni, Pb, and Cr presence in the drinking water of Almaty were identified, with risk values at the majority of sampling sites categorically classified within the “high risk” designation. No substantial differences in carcinogenic risk levels were detected between adults and children. These results underscore the necessity for enhanced water purification methodologies and ongoing surveillance to protect public health. Full article