Search NASA⌕ Search

SEARCH · Search NASA

Results for “Mining”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Data Mining of Polymer Phase Transitions upon Temperature Changes by Small and Wide-Angle X-ray Scattering Combined with Raman Spectroscopy

The complex physical transformations of polymers upon external thermodynamic changes are related to the molecular length of the polymer and its associated multifaceted energetic balance. The understanding of subtle transitions or multistep phase transformation requires real-time phenomenological studies using a multi-technique approach that covers several length-scales and chemical states. A combination of X-ray scattering techniques with Raman spectroscopy and Differential Scanning Calorimetry was conducted to correlate the structural changes from the conformational chain to the polymer crystal and mesoscale organization. Current research applications and the experimental combination of Raman spectroscopy with simultaneous SAXS/WAXS measurements coupled to a DSC is discussed. In particular, we show that in order to obtain the maximum benefit from simultaneously obtained high-quality data sets from different techniques, one should look beyond traditional analysis techniques and instead apply multivariate analysis. Data mining strategies can be applied to develop methods to control polymer processing in an industrial context. Crystallization studies of a PVDF blend with a fluoroelastomer, known to feature complex phase transitions, were used to validate the combined approach and further analyzed by MVA.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Shinkolobweite, from the Shinkolobwe Mine, Democratic Republic of Congo: A New Mineral Containing Uranium in the Rare Pentavalent Oxidation State

ABSTRACT Shinkolobweite, Pb1.333[U5+O(OH)(UO2)5O4.67(OH)5.33](H2O)5, is a new lead uranyl oxide-hydroxide hydrate mineral containing hexavalent and pentavalent uranium from the Shinkolobwe mine, Democratic Republic of Congo. Crystals of shinkolobweite are dark reddish-brown prisms up to 0.5 mm in length, occurring on a matrix of massive uraninite associated with fourmarierite, rutherfordine, soddyite, and sklodowskite. Crystals are translucent with subadamantine luster and light bronze-yellow streak, are flattened on {010}, are elongated on [001], and exhibit the forms {100}, {010}, {101}, and . The mineral is non-fluorescent under both longwave and shortwave ultraviolet illumination. It has a Mohs hardness of ∼2 and exhibits brittle tenacity with perfect cleavage on {010}, imperfect cleavage on {100}, and even fracture. The calculated density is 5.853 g/cm3 based on the empirical formula. Electron probe microanalysis provided the empirical formula Pb1.290U6+4.876U5+1.166O27H16.633 based on 27 O apfu and U5+:U6+ determined by X-ray photoelectron spectroscopy. Shinkolobweite is orthorhombic, superspace group Pnnm(0b0)000, a = 14.4808(4), b = 7.0681(8), c = 11.9423(3) Å, V = 1222.32(15) Å3, modulation wave vector [0 1/3 0], and Z = 2. The structure was refined from 8959 reflections to a final R1 = 0.0736 for all reflections. Uranyl oxide-hydroxide sheets in shinkolobweite adopt the β-U3O8 topology and possess (3 + 1) commensurately modulated ordering that results from the long-range ordering of U5+ and U6+ in the sheet, as well as the position and occupancy of interlayer Pb2+ cations. Observations of a topological transition between α-U3O8 and β-U3O8 type sheets in shinkolobweite supplements our understanding of U5+ mineral oxidation and stability.

Mineralogy↗
DOE OSTI2020

Hydraulic fracturing experiments at 1500 m depth in a deep mine: Highlights from the kISMET project

In support of the U.S. DOE SubTER Crosscut initiative, we established a field test facility in a deep mine and designed and carried out in situ hydraulic fracturing experiments relevant to enhanced geothermal systems (EGS) in crystalline rock to characterize the stress field, understand the effects of rock fabric on fracturing, and gain experience in monitoring using geophysical methods. The project also included pre- and post-fracturing simulation and analysis, and laboratory measurements and experiments. The kISMET (permeability (k) and Induced Seismicity Management for Energy Technologies) site was established in the West Access Drift of the Sanford Underground Research Facility (SURF) 4757 ft (1450 m) below ground (on the 4850 ft level (4850L)) in phyllite of the Precambrian Poorman Formation. We drilled and continuously cored five near-vertical boreholes in a line on 3 m (10 ft) spacing, deviating the two outermost boreholes slightly to create a five-spot pattern around the test borehole centered in the test volume 40 m below the drift invert (floor) at a total depth of ~1490 m (4890 ft). Laboratory measurements of core from the center test borehole showed P-wave velocity heterogeneity along each core indicating strong, fine-scale (~1 cm or smaller) changes in the mechanical properties of the rock. Field measurements of the stress field by hydraulic fracturing showed that the minimum horizontal stress at the kISMET site averages 21.7 MPa (3146 psi) trending approximately N-S (356 degrees azimuth) and plunging slightly NNW at 12°. The vertical and horizontal maximum stresses are similar in magnitude at 42-44 MPa (6090-6380 psi) for the depths of testing, which averaged approximately 1530 m (5030 ft). Hydraulic fractures were remarkably uniform suggesting core-scale and larger rock fabric did not play a role in controlling fracture orientation. Analytical solutions suggest that the fracture radius of the large fracture (stimulation test) was more than 6 m (20 ft), depending on the unknown amount of leak-off.

Oldenburg, C↗
DOE OSTI2021

Systems and processes for recovery of high-grade rare earth concentrate from acid mine drainage

In one aspect, the disclosure relates to a continuous process for treating acid mine drainage while simultaneously recovering a high-grade rare earth preconcentrate suitable for extraction of commercially valuable rare earth oxides. In a further aspect, the preconcentrate is from about 0.1% to 5% rare earth elements on a dry weight basis. In another aspect, the disclosure relates to a method for processing the preconcentrate to generate a pregnant leach solution that does not form gels or emulsions and is suitable for processing via solvent extraction. In another aspect, the disclosure relates to a system and plant for carrying out the disclosed process. In still another aspect, the disclosure relates to a composition containing rare earth elements produced by the process disclosed herein. This abstract is intended as a scanning tool for purposes of searching in the particular art and is not intended to be limiting of the present disclosure.

Ziemkiewicz, Peter F.↗
DOE OSTI2021

Introduction to Fuel Cycle Front End: From Mining Through Utilization

This book chapter introduces the Fuel Cycle Front End: Mining through Utilization Section of this Encyclopedia, providing context for the chapters that follow. It presents an overview of the nuclear fuel cycle and describes design considerations important to fuel technology. This manuscript version of a book chapter from the Encyclopedia of Nuclear Energy (Elsevier, 2021) that was not reviewed in LRS prior to being sent to the book general editor for review or for final publication. It also has not yet been uploaded to SORT/OSTI. The content includes classified subject matter topics, but does not include any classified information (judgement of the author as a Derivative Classifier).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Operation and performance of VRF systems: Mining a large-scale dataset

The energy consumption of air-conditioning systems has gained increasing attention as it contributes significantly to the global building energy use. The variable refrigerant flow (VRF) system is a common air-conditioning system applied widely in residential and office buildings in China. Understanding the actual operation and performance of VRF systems is fundamental for the energy-efficient design and operation of VRF systems. Previous research on VRF system operation used either limited field data covering certain building types and climate zones or used a questionnaire to obtain a larger dataset. However, they did not capture the wide applications of VRF systems quantitatively across all building types, climate zones, and operating conditions. To fill this gap, statistical and clustering analysis was conducted on the newly proposed key performance indicators of approximately 287,000 VRF systems for residential and commercial buildings in all five climate zones in China. In this work, the main findings are: (1) VRF systems are mainly used for cooling in all climate zones in China; (2) among all building types, the duration of use is lowest in residential buildings and highest in hotels and medical buildings; (3) the distribution of the ideal VRF cooling coefficient of performance (COP) is similar across all climate zones and building types; whereas the COPs of ideal VRF heating in the Severe Cold region and Cold regions are lower than those in other climate zones; and (4) partial load operations for VRF systems are common in residential buildings and office buildings due to the part-time-part-space operation mode. These findings can inform the actual application of VRF systems in China, supporting the design, operation, industry standard development, and performance optimization of VRF systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Voltage Mining for (De)lithiation-Stabilized Cathodes and a Machine Learning Model for Li-Ion Cathode Voltage

Advances in lithium-metal anodes have inspired interest in discovery of Li-free cathodes, most of which are natively found in their charged state. This is in contrast to today's commercial lithium-ion battery cathodes, which are more stable in their discharged state. In this study, we combine calculated cathode voltage information from both categories of cathode materials, covering 5577 and 2423 total unique structure pairs, respectively. The resulting voltage distributions with respect to the redox pairs and anion types for both classes of compounds emphasize design principles for high-voltage cathodes, which favor later Period 4 transition metals in their higher oxidation states and more electronegative anions like fluorine or polyanion groups. Generally, cathodes that are found in their charged, delithiated state are shown to exhibit voltages lower than those that are most stable in their lithiated state, in agreement with thermodynamic expectations. Deviations from this trend are found to originate from different anion distributions between redox pairs. In addition, a machine learning model for voltage prediction based on chemical formulas is trained and shows state-of-the-art performance when compared to two established composition-based ML models for material properties predictions, Roost and CrabNet.

25 ENERGY STORAGE↗
DOE OSTI2026

Unsupervised atomic data mining via multi-kernel graph autoencoders for machine learning force fields

Constructing a chemically diverse dataset while avoiding sampling bias is critical to training efficient and generalizable force fields. However, in computational chemistry and materials science, many common dataset generation techniques are prone to oversampling regions of the potential energy surface. Furthermore, these regions can be difficult to identify and isolate from each other or may not align well with human intuition, making it challenging to systematically remove bias in the dataset. While traditional clustering and pruning (down-sampling) approaches can be useful for this, they can often lead to information loss or a failure to properly identify distinct regions of the potential energy surface due to difficulties associated with the high dimensionality of atomic descriptors. In this work, we introduce the Multi-kernel Edge Attention-based Graph Autoencoder (MEAGraph) model, an unsupervised approach for analyzing atomic datasets. MEAGraph combines multiple linear kernel transformations with attention-based message passing to capture geometric sensitivity and enable effective dataset pruning without relying on labels or extensive training. Demonstrated applications on niobium, tantalum, and iron datasets show that MEAGraph efficiently groups similar atomic environments, allowing for the use of basic pruning techniques for removing sampling bias. This approach provides an effective method for representation learning and clustering that can be used for data analysis, outlier detection, and dataset optimization.

Materials science↗
DOE OSTI2022

Integrated CO 2 -facilitated Hydrometallurgical and Electrochemical Technology for Sustainable Mining and Recovery of Critical Elements from Wastes and Ashes

The availability of critical materials and other metals is very important for our national security and economic growth since they are widely used in defense and energy applications including batteries and wind turbines. Unfortunately, high grade ores have become scarce and their productions is dominated by limited countries. Thus, there is a strong need to obtain these materials from domestic sources. Municipal wastes are great candidates since they often contain high concentrations of metals. Since the metals in wastes and waste ashes are not in the form found in natural ores and contain a wide range of impurities, conventional extraction processes would not be effective. Thus, our project has developed an innovative MIDAS process based on the integrated CO2-facilitated hydrometallurgical and electrochemical technology that can effectively recover critical materials and metals from waste ashes while minimizing the environmental impacts. We have (i) characterized waste ashes to understand their physico-chemical properties, (ii) developed green solvent systems for hydrometallurgical extraction of critical elements and metals from waste ashes, (iii) explored electrochemical interfaces to refine the extracted metals.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Data Mining of Groundwater to Identify MAGs with Methane, Propane and Toluene Monooxygenases

Whole genome sequencing datasets, involving more than 600 groundwater samples, from nine countries, were analyzed to identify metagenome assembled genomes (MAGs) containing full operons for propane monooxygenase, soluble methane monooxygease, toluene monooxygenase and particulate ammonia/methane monooxygenase. The enzymes encoded by these genes are a focus of interest because of their ability to degrade common groundwater contaminants. Due to the large amount of data, sequence analyses involved more than 80 individual KBase narratives. The approach followed the KBase tutorial called "Metagenome-Assembled Genome Extraction from a Compost Microbiome Enrichment" The generated MAGs were exported from each individual narrative into separate summary KBase narratives for each monooxygenase. Three KBase narratives were generated for particulate ammonia/methane monooxygenase, due to the large number of MAGs identified.

59 BASIC BIOLOGICAL SCIENCES↗