Uranium fell to 76.20 USD/Lbs on September 5, 2025, down 0.65% from the previous day. Over the past month, Uranium's price has risen 5.32%, but it is still 4.69% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Uranium - values, historical data, forecasts and news - updated on September of 2025.

This dataset provides values for URANIUM reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Index Time Series for Global X Uranium Index ETF. The frequency of the observation is daily. Moving average series are also typically included. NA

Uranium is a common element throughout the Earth’s crust, soils, and oceans. Uranium resources are naturally occurring deposits that may have a sufficient concentration of uranium to support mining operations. Canada has about 8% of the world’s unmined uranium resources, but accounts for some 25% of the global primary uranium production. Canada’s uranium mines are located in the Athabasca Basin of northern Saskatchewan, which has ore grades as high as 21% uranium metal, an order of magnitude larger than any other deposits in the world. The nuclear industry provides about 15% of Canada’s electrical power (50% of Ontario’s). The map shows districts with potential for uranium development, small occurrences of uranium, locations of uranium mines and facilities, and locations of nuclear facilities that generate electrical power.

Index Time Series for Global X Uranium UCITS ETF USD Acc CHF. The frequency of the observation is daily. Moving average series are also typically included. NA

Some of the highest grade uranium (U) deposits in the United States are hosted by solution-collapse breccia pipes in the Grand Canyon region of northern Arizona. These structures are named for their vertical, pipe-like shape and the broken rock (breccia) that fills them. Hundreds, perhaps thousands, of these structures exist. Not all of the breccia pipes are mineralized; only a small percentage of the identified breccia pipes are known to contain an economic uranium deposit. An unresolved question is how many undiscovered U-bearing breccia pipes of this type exist in northern Arizona, in the region sometimes referred to as the “Arizona Strip”. Two principal questions remain regarding the breccia pipe U deposits of northern Arizona are: (1) What processes combined to form these unusual structures and their U deposits? and (2) How many undiscovered U deposits hosted by breccia pipes exist in the region? A piece of information required to answer these questions is to define the area where these types of deposits could exist based on available geologic information. In order to determine the regional processes that led to their formation, the regional distribution of U-bearing breccia pipes must be considered. These geospatial datasets were assembled in support of this goal.

This time I deided to pay attention on the changes in metal prices within last 30 year. The most popular and interesting in visualization metals prices were tacken: Gold, Aluminium, Silver, Uranium and Nickel Don't forget to check out my previous "Price Changes within last 30 Years" datasets: 🌽 Cerial Prices Changes Within Last 30 Years ☕Coffee, Rice and Beef Prices Changes for 30 Years

Jeu de données extrait du portail Kapsarc et utilisé dans le cours ODS Academy "Choisir le bon type de visualisation pour vos données".

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Uranium Energy (YCA): The Sun's Yellow Cake, or Just a Fool's Gold Investment?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Nuclear Energy Index rose to 40.68 USD on September 5, 2025, up 0.87% from the previous day. Over the past month, Nuclear Energy Index's price has fallen 1.48%, but it is still 75.72% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Nuclear Energy Index.

Basalt formation waters collected from Hole 504B at sub-basement depths of 194, 201, 365, and 440 meters show inverse linear relationships between 87Sr/86Sr and Ca, 87Sr/86Sr and Sr, and K and Ca. If the Ca content of a fully reacted formation water end-member is assumed to be 1340 ppm, the K, Sr, and 87Sr/86Sr values for the end-member are 334 ppm, 7.67 ppm, and 0.70836, respectively. With respect to contemporary seawater at Hole 504B, K is depleted by 13%, Sr is enriched by 2.7%, and 87Sr/86Sr is depleted by 0.8%. The Sr/Ca ratio of the formation water (0.0057) is much lower than that of seawater (0.018) but is similar to the submarine hot spring waters from the Galapagos Rift and East Pacific Rise and to geothermal brines from Iceland. At the intermediate temperatures represented by the Hole 504B formation waters (70°-105°C), the interaction between seawater and the ocean crust produces large solution enrichments in Ca, the addition of a significant basalt Sr isotope component accompanied by only a minor elemental Sr component, and the removal from solution of seawater K. The Rb, Cs, and Ba contents of the formation waters appear to be affected by contamination, possibly from drilling muds. Sediment depth is given in mbsf. Concentrations are corrected (+0.67%) for HCl dilution.

Data was compiled from published sources by US Geological Survey geoscientists Mark J. Mihalasky, Susan M. Hall and Robert A. Zielinski. This dataset was provided to the U.S. Energy Information Administration in February of 2019 to facilitate updating of national uranium resource distribution maps. Some sedimentary phosphate deposits contain trace uranium. Historically when uranium prices were high enough, this uranium was extracted as part of the phosphate mining process. In 2019 no uranium is being commercially extracted as part of phosphate mining in the United States. The location of uraniferous phosphate deposits within the United States is shown on this layer.Details and location information is from:DeVoto, R.H.; Stevens, D.N. (eds.), 1979, Uraniferous phosphate resources and technology and economics of uranium recovery from phosphate resources, United States and free world; GJBX-110(79), Volume 1, 724 p. Volume 2, 50 p. plus plates.

This data release compiles the whole-rock geochemistry, X-ray diffraction, and electron microscopy analyses of samples collected from the uranium ore bodies of two mined-out deposits in the Grand Canyon region of northwestern Arizona - the Hack II and Pigeon deposits. The samples are grab samples of ore collected underground at each mine by the U.S. Geological Survey (USGS) during the mid-1980s, while each mine was active. The Hack II and Pigeon mines were remediated after their closure, so these data, analyses of samples in the archives of the USGS, are provided as surviving, although limited representations of these ore bodies. The Hack II and Pigeon deposits are similar to numerous other uranium deposits hosted by solution-collapse breccia pipes in the Grand Canyon region of northwest Arizona. The uranium-copper deposits occur within matrix-supported columns of breccia (a "breccia pipe") that formed by solution and collapse of sedimentary strata (Wenrich, 1985; Alpine, 2010). The regions north and south of the Grand Canyon host hundreds of solution-collapse breccia pipes (Van Gosen and others, 2016). Breccia refers to the broken rock that fills these features, and pipe refers to their vertical, pipe-like shape. The breccia pipes average about 300 ft (90 m) in diameter and can extend vertically for as much as 3,000 ft (900 m), from their base in the Mississippian Redwall Limestone to as stratigraphically high as the Triassic Chinle Formation. The breccia fragments are blocks and pieces of rock units that have fallen downward, now resting below their original stratigraphic level. In contrast to many other types of breccia pipes, there are no igneous rocks associated with the northwestern Arizona breccia pipes, nor have igneous processes contributed to their formation. Many of these breccia pipes contain concentrated deposits of uranium, copper, arsenic, barium, cobalt, lead, molybdenum, nickel, antimony, strontium, vanadium, and zinc minerals (Wenrich, 1985), which is reflected in this data set. The Hack II and Pigeon mines were two of thirteen breccia pipe deposits in the Grand Canyon region mined for uranium from the 1950s to present (2020) (Alpine, 2010; Van Gosen and others, 2016). While hundreds of breccia pipes in the region have been identified (Van Gosen and others, 2016), six decades of exploration across the region has found that most are not mineralized or substantially mineralized, and only a small percentage of the breccia pipes contain economic uranium deposits. The most recent mining operation in a breccia pipe deposit in the region is the Canyon mine, located about 6.1 miles (10 km) south-southeast of Tusayan, Arizona. In 2018, Energy Fuels completed a mine shaft and other mining facilities at the Canyon deposit, a copper- uranium-bearing breccia pipe (Van Gosen and others, 2020); however, this mining operation is currently (2020) inactive, awaiting higher market prices for uranium oxide. The Hack II deposit is one of four breccia pipes mined in Hack Canyon near its intersection with Robinson Canyon (Chenoweth, 1988; Otton and Van Gosen, 2010), approximately 30 miles (48 km) southwest of Fredonia and 9 miles (14.5 km) north-northwest of Kanab Creek. Hack Canyon incised and exposed part of the "Hacks" (or "Hack Canyon") breccia pipe, which was discovered and mined as a surface mine in the early 1900s for copper and silver. The original Hacks mine and adjacent Hack I deposit were later mined underground for uranium from 1950 to 1954 (Chenoweth, 1988). The Hack II deposit was discovered in the late 1970s along Hack Canyon about 1 mile (1.6 km) upstream of the Hacks and Hack I mines. The Hack II mine is located at latitude 36.58219 north, longitude -112.81059 west (datum of WGS84). Mining began at Hack II in 1981 and ended in May 1987. The USGS collected the ore samples reported in this data release in 1984 from underground exposures in the Hack II mine while it was in operation. Reclamation of the four mines in the area (Hacks, Hack I, Hack II, and Hack III) was planned and completed from March 1987 to April 1988, including infilling of the shafts and adits. Total production from the Hack II mine was reported as 7.00 million pounds (3.2 million kilograms) of uranium oxide from ore that had an average grade of 0.70 percent uranium oxide. This represents the largest uranium production from a breccia pipe deposit in the Grand Canyon region thus far (Otton and Van Gosen, 2010). The Pigeon mine was discovered along Kanab Creek in 1980. The site was prepared and developed from 1982 to 1984, and mining began in December 1984. The pipe was mined out in late 1989 and reclamation begun shortly thereafter. The former mine site is located at latitude 36.7239 north, longitude -112.5275 south (datum of WGS84). The Pigeon mine reportedly produced 5.7 million pounds (2.6 million kilograms) of ore that had an average grade of 0.65 percent uranium oxide. The five Pigeon deposit samples reported in this data release were collected by the USGS from underground exposures in the Pigeon mine in 1985, while the mine was in operation. Fourteen samples of Hack II ore and two samples of Pigeon ore were analyzed for major and trace elements by a laboratory contracted by the USGS. Concentrations for 59 elements were determined by Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES). Additionally, carbonate carbon (inorganic carbon), total carbon, total sulfur, iron oxide, and mercury concentrations were determined using other element-specific analytical techniques. These 16 samples and an additional four Hack II ore samples and three Pigeon ore samples were analyzed by X-ray diffraction (XRD) to determine their mineralogy. Polished thin sections cut from six of the Hack II ore samples were examined using a scanning electron microscope equipped with an energy dispersive spectrometer (SEM-EDS) to identify the ore minerals and observe their relationships at high magnification. The EDS vendor's auto identification algorithm was used for peak assignments; the user did not attempt to verify every peak identification. The spectra for each EDS measurement are provided in separate documents in Portable Data Format (pdf), one document for each of the six samples that were examined by SEM-EDS. The interpreted mineral phase(s), which is based solely on the judgement of the user, is given below each spectrum. References cited above: Alpine, A.E., ed., 2010, Hydrological, geological, and biological site characterization of breccia pipe uranium deposits in northern Arizona: U.S. Geological Survey Scientific Investigations Report 2010-5025, 353 p., 1 plate, scale 1:375,000. Available at http://pubs.usgs.gov/sir/2010/5025/ Chenoweth, W.L., 1988, The production history and geology of the Hacks, Ridenour, Riverview and Chapel breccia pipes, northwestern Arizona: U.S. Geological Survey Open-File Report 88-648, 60 p. Available at https://pubs.usgs.gov/of/1988/0648/report.pdf Otton, J.K., and Van Gosen, B.S., 2010, Uranium resource availability in breccia pipes in northern Arizona, in Alpine, A.E., ed., Hydrological, geological, and biological site characterization of breccia pipe uranium deposits in northern Arizona: U.S. Geological Survey Scientific Investigations Report 2010-5025, p. 23-41. Available at http://pubs.usgs.gov/sir/2010/5025/ Van Gosen, B.S., Johnson, M.R., and Goldman, M.A., 2016, Three GIS datasets defining areas permissive for the occurrence of uranium-bearing, solution-collapse breccia pipes in northern Arizona and southeast Utah: U.S. Geological Survey data release, https://doi.org/10.5066/F76D5R3Z Van Gosen, B.S., Benzel, W.M., and Campbell, K.M., 2020, Geochemical and X-ray diffraction analyses of drill core samples from the Canyon uranium-copper deposit, a solution-collapse breccia pipe, Grand Canyon area, Coconino County, Arizona: U.S. Geological Survey data release, https://doi.org/10.5066/P9UUILQI Wenrich, K.J., 1985, Mineralization of breccia pipes in northern Arizona: Economic Geology, v. 80, no. 6, p. 1722-1735, https://doi.org/10.2113/gsecongeo.80.6.1722

Uranium concentrations in a large number of marine sediment samples of different types with world-wide spatial distribution have been determined using the rapid, precise and nondestructive technique of counting the delayed neutrons emitted during U235 fission induced with thermal neutrons. Several interesting relationships were apparent. 1) A direct proportionality was observed between percentage of organic carbon and uranium in sediments deposited in an anoxic environment in the Pettaquamscutt River in Rhode Island with concentrations ranging from 7 per cent organic carbon and 7 ppm uranium to 14 per cent organic carbon and 30 ppm uranium. A similar relationship was found in cores of sediments deposited on the Sigsbee Knolls in the Gulf of Mexico. 2) For manganese nodules a direct relationship can be seen between uranium and calcium concentrations and both decrease with increasing depth of deposition. For nodules from 4500 m in the Pacific, concentrations are 3 ppm uranium and 0.3 per cent calcium compared with 14 ppm uranium and 1.5 per cent calcium at 1000 m. 3) Relatively high uranium concentrations were observed in carbonates deposited in the deepest parts of the Gulf of Mexico, with the >88 ? carbonate fraction in Sigsbee Knoll cores having as much as 1.20 ppm. A model to explain the observed variations must include uranium enrichment in near shore environments via an anoxic pathway, followed by redeposition in a deep ocean environment with dilution either by low-uranium-bearing foraminiferal or silicious oozes or, along the continental margins, dilution with high-uranium-bearing carbonate sands.

In situ recovery (ISR) uranium mining is a technique in which uranium is extracted by a series of injection and recovery wells developed in a permeable sandstone host rock. Chemical constituents (lixiviants) are added to groundwater injection wells to mobilize uranium into groundwater. Before mining, baseline water quality is measured by sampling groundwater from the aquifer intended to be mined and over and underlying units over a geographic area that reflects the proposed mine location. After mining, groundwater is restored using a variety of techniques intended to return groundwater quality to as close to baseline as practicable. After groundwater has been restored, groundwater quality is monitored to determine if the groundwater chemistry has stabilized. The impact of ISR mining on groundwater is poorly understood because records archiving these impacts are difficult to locate. The USGS collected as many historic records describing ISR well fields as they could locate between 2008 and 2014. This data release summarizes historic records from ISR mines developed in Texas and compiled into spreadsheets by USGS mostly from records maintained by the Texas Commission on Environmental Quality.

The Snake River Plain (SRP), Idaho, hosts potential geothermal resources due to elevated groundwater temperatures associated with the thermal anomaly Yellowstone-Snake River hotspot. Project HOTSPOT has coordinated international institutions and organizations to understand subsurface stratigraphy and assess geothermal potential. Over 5.9km of core were drilled from three boreholes within the SRP in an attempt to acquire continuous core documenting the volcanic and sedimentary record of the hotspot: (1) Kimama, (2) Kimberly, and (3) Mountain Home. The Kimberly drill hole was selected to document continuous volcanism when analysed in conjunction with the Kimama and is located near the margin of the plain.

Data submitted by project collaborator Doug Schmitt, University of Alberta SGY file of vertical seismic profile data (197-285) FAR

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Paleoceanography. The data include parameters of paleoceanography with a geographic location of Global. The time period coverage is from 23500 to 0 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

Some populations quickly adapt to strong and novel selection pressures caused by anthropogenic stressors. However, this short-term evolutionary response to novel and harsh environmental conditions may lead to adaptation costs, and evaluating these costs is important if we want to understand the evolution of resistance to anthropogenic stressors. In this experimental evolution study, we exposed Caenorhabditis elegans populations to uranium (U populations), salt (NaCl populations), alternating uranium/salt treatments (U/NaCl populations), and to a control environment (C populations), over 22 generations. In parallel, we ran common-garden and reciprocal-transplant experiments to assess the adaptive costs for populations that have evolved in the different environmental conditions. Our results showed rapid evolutionary changes in life history characteristics of populations exposed to the different pollution regimes. Furthermore, adaptive costs depended on the type of pollutant: pollution-adapted populations had lower fitness than C populations, when the populations were returned to their original environment. Fitness in uranium environments was lower for NaCl populations than for U populations. In contrast, fitness in salt environments was similar between U and NaCl populations. Moreover, fitness of U/NaCl populations showed similar or higher fitness in both the uranium and the salt environments compared to populations adapted to constant uranium or salt environments. Our results show that adaptive evolution to a particular stressor, can lead to either adaptive costs or benefits once in contact with another stressor. Furthermore, we did not find any evidence that adaptation to alternating stressors was associated with additional adaption costs. This study highlights the need to incorporate adaptive cost assessments when undertaking ecological risk assessments of pollutants.

We provide new measurements of wavenumbers and line identifications of 10100 UI and UII near-infrared (NIR) emission lines between 2500cm^-1^ and 12000cm^-1^ (850-4000nm) using archival Fourier transform spectrometer spectra from the National Solar Observatory. This line list includes isolated uranium lines in the Y, J, H, K, and L bands (0.9-1.1um, 1.2-1.35um, 1.5-1.65um, 2.0-2.4um, and 3.0-4.0um, respectively), and provides six times as many calibration lines as thorium in the NIR spectral range. The line lists we provide enable inexpensive, commercially available uranium hollow cathode lamps to be used for high-precision wavelength calibration of existing and future high-resolution NIR spectrographs.

This GIS dataset contains polygon features representing the boundaries of the six Abandoned Uranium Mines (AUM) Regions, including: Central, Eastern, Northern, North Central, Southern, and Western Regions. These regions comprise the parts of the Navajo Nation where abandoned uranium mines are located and does not encompass the entire Navajo Nation. Each AUM Region is comprised of many Chapters. Each included Chapter has at least one AUM within its boundaries.