Rapid extraction and assay of uranium from environmental surface samples
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Experimental observation of metal-insulator transition in epitaxial films of vanadium dioxide is reported. Hemispherical angle-resolved light scattering technique is applied for statistical analysis of the phase transition processes on mesoscale. It is shown that the thermal hysteresis strongly depends on spatial frequency of surface irregularities. The transformation of scattering indicatrix depends on sample morphology and is principally different for the thin films with higher internal elastic strain and for the thicker films where this strain is suppressed by introduction of misfit dislocations. The evolution of scattering indicatrix, fractal dimension, surface power spectral density, and surface autocorrelation function demonstrates distinctive behavior which elucidates the influence of structural defects and strain on thermal hysteresis, twinning of microcrystallites, and domain formation during the phase transition.
Boron carbide crystals have been obtained in the entire compositional range according to the phase diagram by self-propagating high-temperature synthesis (SHS). Based on the results of X-ray diffraction investigations, the samples were characterized by the unit-cell metric and reflection half-width in the entire range of carbon concentrations. A significant spread in the boron carbide unit-cell parameters for the same carbon content is found in the data in the literature; this spread contradicts the structural concepts for covalent compounds. The SHS samples have not revealed any significant spread in the unit-cell parameters. Structural analysis suggests that the spread of parameters in the literary data is related to the unique process of ordering of carbon atoms in the boron carbide structure.
TOF-ND elastic scattering of thermal neutrons offers some important advantages over X-ray diffraction (XRD), X-ray fluorescence (XRF), and metallography for the study of archaeological and numismatic problems. Traditional analytical methods are usually destructive and often probe only the surface. Neutrons deeply penetrate samples, simultaneously giving nondestructive bulk information about the crystal structure, composition, and texture (alignment of crystallites) from which thermomechanical manufacturing processes (e.g., cast, struck, or rolled) may be inferred. An analysis of the metal composition and minting processes used for making ancient Judaean bronze and leaded bronze coins from first century BCE and CE is used as a case study. One of the first ND analyses of the temperature used for striking bronze coins is also presented.
Genetic manipulation of crops to increase the presence of desirable traits has been critical to increasing agricultural productivity. These changes have primarily involved modification of the plant’s DNA sequence. However, there is increasing evidence that environmental responses are also mediated by epigenetics, which involves heritable changes without changes in DNA sequence. Epigenetic changes have been shown to play a major role in regulating plant responses to drought, an increasing problem worldwide due to climate change. In general, exposure of plants to water limitation triggers epigenetic changes, which include remodeling of chromatin, the network of DNA, RNA and various proteins making up chromosomes, and related changes in regulatory mechanisms. EPICON’s efforts focus on unraveling the role epigenetic signals play in acclimation to and recovery from drought through effects on individual transcription factors or transcriptional networks that direct entire metabolic pathways. To achieve this goal we will follow responses to water deprivation in sorghum, a widely cultivated cereal with recognized drought tolerance. In EPICON’s field trials, sorghum will be grown under controlled irrigation conditions. Leaf and root samples will be taken to perform molecular phenotyping to track changes in epigenetic, transcriptomic, metabolomic and proteomic footprints. Analysis of this data will provide a better understanding of the epigenetic processes related to drought tolerance, leading to our ultimate goal of identifying transcriptional regulators and pathways controlling drought resistance. The identified genetic targets and their regulatory pathways will be used in future efforts to improve growth of sorghum and other crops in the field and in marginal lands under water-limiting conditions.
We introduce a computational analysis workflow to access properties of solid objects using nondestructive imaging techniques that rely on X-ray imaging. The goal is to process and quantify structures from material science sample cross sections. The algorithms can differentiate the porous media (high density material) from the void (background, low density media) using a Boolean classifier, so that we can extract features, such as volume, surface area, granularity spectrum, porosity, among others. Our workflow, Quant-CT, leverages several algorithms from ImageJ, such as statistical region merging and 3D object counter. It also includes schemes for bilateral filtering that use a 3D kernel, for parallel processing of sub-stacks, and for handling over-segmentation using histogram similarities. The Quant-CT supports fast user interaction, providing the ability for the user to train the algorithm via subsamples to feed its core algorithms with automated parameterization. Quant-CT plugin is currently available for testing by personnel at the Advanced Light Source and Earth Sciences Divisions and Energy Frontier Research Center (EFRC), LBNL, as part of their research on porous materials. The goal is to understand the processes in fluid-rock systems for the geologic sequestration of CO2, and to develop technology for the safe storage of CO2 in deep subsurface rock formations. We describe our implementation, and demonstrate our plugin on porous material images. This paper targets end-users, with relevant information for developers to extend its current capabilities.
High-pressure and temperature deformation experiments interfaced with acoustic emission (AE) monitoring have been conducted to study transformational faulting in Mn 2 GeO 4 olivine, which transforms to the β phase, isostructural to wadsleyite. Metastable Mn 2 GeO 4 olivine exhibits a marked embrittlement behavior at temperatures between 800 and 1100 K, emitting numerous AEs. At each temperature, brittle deformation is characterized by a two-stage process: (1) a “preparation” stage with numerous diffusedly located low-magnitude AEs and large b values (>2), and (2) a failure stage where larger-magnitude AEs form a planar distribution with b values about 1. Microstructure analysis reveals extensive kink band development in olivine grains in the recovered samples. Kink band boundaries (KBBs), with a typical thickness of ∼100 nm, are filled with a nanometric β-Mn 2 GeO 4 “gouge”. A dense array of secondary shear localizations is often present within the kink bands, suggesting significant shear deformation therein. The combined observations suggest that faulting in metastable Mn 2 GeO 4 olivine is a self-similar process, from grain-scale to the sample-scale. Both observed embrittlement behavior and the microstructure of metastable Mn 2 GeO 4 olivine are essentially identical to those in Mg 2 GeO 4 olivine we have reported previously, indicating that the physical mechanism of faulting in metastable olivine is insensitive to the specific crystallographic structure of the high-pressure phase. The low b values (about 1) observed in the faulting process in our experiments are similar to those of deep focus earthquakes in cold subduction zones. Our observed mechanism explains deep focus seismicity in cold metastable mantle wedges, provided that the self-similarity assumption holds to geological scales.
H-Canyon Nuclear and Criticality Safety Engineering has completed development of the documentation necessary to complete the September 30, 2014, H-Canyon PBI milestone that states: Complete the analytical work to develop proposed HFIR Criticality Safety Limits associated with receipt and dissolving of HFIR material. Attached to this memorandum are the following: (1) Attachment 1- HFIR Dissolution Nuclear Criticality Analysis; (2) Attachment 2 - SCALE 5/KENO VI sample input As documented in Attachment 1, the safety of HFIR dissolution in H-Canyon has been evaluated. Due to the composition and geometry of the HFIR elements and the chemistry of the dissolution process, there are no credible criticality events associated with HFIR dissolution, with the exception of potential Pu polymerization. There are no mass, concentration, or soluble poison CSLs required for HFIR dissolution in H-Canyon. If SRNL, in the development of the HFIR flow sheet, determines that Pu polymerization is a credible event, a minimum nitric acid PPL and controls will be developed. However, there is no analysis or CSLs needed for this event. The boron in the borated stainless steel posts is not required, and, therefore, blackness testing is not required for criticality safety.
The construction of highly coherent X-ray sources, combined with next-generation detectors that are larger and faster, has enabled new research opportunities across the scientific landscape. Among the techniques that benefit most from these advancements is X-ray photon correlation spectroscopy (XPCS), where faster acquisition unlocks the ability to study faster dynamics within samples. However, faster acquisition on larger detectors also introduces unprecedented challenges for online data processing and offline data storage. Such challenges are particularly prominent for XPCS, where real time analyses require simultaneous calculation of all the previously acquired data in the time series. We present a homomorphic compression scheme to effectively reduce the computational time and memory space required for XPCS analysis. Leveraging similarities in the mathematical expression between a matrix-based compression algorithm and the correlation calculation, our approach allows direct operation on the compressed data without their decompression. The offline compression scheme extends storage capacity by a factor of 40 while preserving key features in the lossy compressed data. Meanwhile, the online compression scheme reduces the computational time to below 1 ms, enabling real time calculation of the correlation functions at kHz framerate. Our demonstration of a homomorphic compression of scientific data provides an effective solution to the big data challenge at coherent light sources. Beyond the example shown in this work, the framework can be extended to facilitate real-time operations directly on a compressed data stream for other techniques.
In this paper, we introduce a neural learning-based approach to blind source separation for detection of material flaws in pulsed thermography (PT) images. This approach can be used to detect internal defects (pores) in metallic Additively Manufactured (AM) materials. Such defects occur in high-strength alloys produced with direct laser sintering AM method for nuclear energy applications. Pulsed thermal imaging system utilizes a high intensity flash lamp to rapidly heat surface of sample, a high sensitivity infrared camera to capture data of surface temperature variations. The data cube obtained with PT (stack of surface temperature images at different times) can be analyzed with image processing algorithms to detect material defects. Compared with conventional nondestructive evaluation (NDE) methods, such as digital radiography and ultrasonic testing, the PT pulsed infrared thermal detection technique has advantages of one-sided non-contact measurements, fast processing of large sample areas captured in one image. Detection of small material defects requires finding features in thermal images, which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with the photothermic, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.
The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key progress in modeling and experimental approaches towards the characterization of chemical and physical phenomena that could impact the long-term safety assessment of heat-generating nuclear waste disposition in deep clay/shale/argillaceous rock. International collaboration activities such as heater tests and postmortem analysis of samples recovered from these have elucidated key information regarding changes in the engineered barrier system (EBS) material exposed to years of thermal loads. Chemical and structural analyses of sampled bentonite material from such tests has as well as experiments conducted on these are key to the characterization of thermal effects affecting bentonite clay barrier performance and the extent of sacrificial zones in the EBS during the thermal period. Thermal, hydrologic, and chemical data collected from heater tests and laboratory experiments has been used in the development, validation, and calibration of THMC simulators to model near-field coupled processes. This information leads to the development of simulation approaches (e.g., continuum vs. discrete) to tackle issues related to flow and transport at various scales of the host-rock and EBS design concept. Consideration of direct disposal of large capacity dual-purpose canisters (DPCs) as part of the back-end SNF waste disposition strategy has generated interest in improving our understanding of the effects of elevated temperatures on the EBS design. This is particularly important for backfilled repository concepts where temperature plays a key role in the EBS behavior and long-term performance. This report describes multiple R&D efforts on disposal in argillaceous geologic media through development and application of coupled THMC process models, experimental studies on clay/metal/cement barrier and host-rock (argillite) material interactions, molecular dynamic (MD) simulations of water transport during (swelling) clay dehydration, first-principles studies of metaschoepite (UO 2 corrosion product) stability, and advances in thermodynamic plus surface complexation database development. Drift-scale URL experiments provides key data for testing hydrological-chemical (HC) model involving strong couplings of fluid mixing and barrier material chemical interactions. The THM modeling focuses on heater test experiments in argillite rock and gas migration in bentonite as part of international collaboration activities at underground research laboratories (URLs). In addition, field testing at an URL involves in situ analysis of fault slip behavior and fault permeability. Pore-scale modeling of gas bubble migration is also being investigated within the gas migration modeling effort. Interaction experiments on bentonite samples from heater test under ambient and elevated temperatures permit the evaluation of ion exchange, phase stability, and mineral transformation changes that could impact clay swelling. Advances in the development, testing, and implementation of a spent nuclear fuel (SNF) degradation model coupled with canister corrosion focus on the effects of hydrogen gas generation and its integration with Geologic Disposal Safety Assessment (GDSA). GDSA integration activities includes evaluation of groundwater chemistries in shale formations.
A series of numerical test cases reflecting broad and realistic ranges of geological formation properties was developed to systematically evaluate and compare the impacts of those properties on geomechanical responses to CO2 injection. A coupled hydro-geomechanical subsurface transport simulator, STOMP (Subsurface Transport over Multiple Phases), was adopted to simulate the CO2 migration process and geomechanical behaviors of the surrounding geological formations. A quasi-Monte Carlo sampling method was applied to efficiently sample a high-dimensional parameter space consisting of injection rate and 14 subsurface formation properties, including porosity, permeability, entry pressure, irreducible gas and aqueous saturation, Young’s modulus, and Poisson’s ratio for both reservoir and caprock. Generalized cross-validation and analysis of variance methods were used to quantitatively measure the significance of the 15 input parameters. Reservoir porosity, permeability, and injection rate were found to be among the most significant factors affecting the geomechanical responses to the CO2 injection. We used a quadrature generalized linear model to build a reduced-order model that can estimate the geomechanical response instantly instead of running computationally expensive numerical simulations.
X-ray fluorescence near total reflection (XFNTR) is the primary technique used to measure the element-specific interfacial density of ions at liquid−liquid interfaces. Fluorescence from ions in the bulk liquids can complicate the determination of the interfacial density; consequently, measurements have been previously limited to samples without ions in the upper phase and with concentrations on the order of 10 μM or less in the lower phase. We modify the analysis of XFNTR data to account for ions in both bulk phases, then demonstrate its use in the context of rare-earth separations processes. In a model of ion stripping (i.e., back-extraction), dodecane solutions of di(2-ethylhexyl)- phosphoric acid (HDEHP) loaded with Eu(III) at the 1 mM level are placed in contact with either pure water or aqueous solutions of nitric or citric acid at pH 3. XFNTR measurements of equilibrated, quiescent samples reveal that citric acid solutions produce a disproportionately large depletion of ions from the interface compared to that from the bulk organic solution, whereas stripping by pure water or nitric acid solutions is negligible. As a result, this advance in the methodology of XFNTR may have broad applicability to the investigation of metal ions in chemical and biological processes at liquid−liquid interfaces.
Typically, the greatest risk in developing accurate cost estimates for the remediation of hazardous, toxic, and radioactive waste sites is the uncertainty in the estimated volume of contaminated media requiring remediation. Efforts to address this risk in the remediation cost estimate can result in large cost contingencies that are often considered unacceptable when budgeting for site cleanups. Such was the case for the Luckey Formerly Utilized Sites Remedial Action Program (FUSRAP) site near Luckey, Ohio, which had significant uncertainty surrounding the estimated volume of site soils contaminated with radium, uranium, thorium, beryllium, and lead. Funding provided by the American Recovery and Reinvestment Act (ARRA) allowed the U.S. Army Corps of Engineers (USACE) to conduct additional environmental sampling and analysis at the Luckey Site between November 2009 and April 2010, with the objective to further delineate the horizontal and vertical extent of contaminated soils in order to reduce the uncertainty in the soil volume estimate. Investigative work included radiological, geophysical, and topographic field surveys, subsurface borings, and soil sampling. Results from the investigative sampling were used in conjunction with Argonne National Laboratory's Bayesian Approaches for Adaptive Spatial Sampling (BAASS) software to update the contaminated soil volume estimate for the site. This updated volume estimate was then used to update the project cost-to-complete estimate using the USACE Cost and Schedule Risk Analysis process, which develops cost contingencies based on project risks. An investment of $1.1 M of ARRA funds for additional investigative work resulted in a reduction of 135,000 in-situ cubic meters (177,000 in-situ cubic yards) in the estimated base volume estimate. This refinement of the estimated soil volume resulted in a $64.3 M reduction in the estimated project cost-to-complete, through a reduction in the uncertainty in the contaminated soil volume estimate and the associated contingency costs. (authors)
We present the first application of the COSMOGLOBE analysis framework by analyzing nine-year WMAP time-ordered observations that uses similar machinery to that of BEYONDPLANCK for the Planck Low Frequency Instrument (LFI). We analyzed only the Q-band (41 GHz) data and report on the low-level analysis process based on uncalibrated time-ordered data to calibrated maps. Most of the existing BEYONDPLANCK pipeline may be reused for WMAP analysis with minimal changes to the existing codebase. The main modification is the implementation of the same preconditioned biconjugate gradient mapmaker used by the WMAP team. Producing a single WMAP Q1-band sample requires 22 CPU-hrs, which is slightly more than the cost of a Planck 44 GHz sample of 17 CPU-hrs; this demonstrates that a full end-to-end Bayesian processing of the WMAP data is computationally feasible. In general, our recovered maps are very similar to the maps released by the WMAP team, although with two notable differences. In terms of temperature, we find a ~2 μK quadrupole difference that most likely is caused by different gain modeling, while in polarization we find a distinct 2.5 μK signal that has been previously referred to as poorly measured modes by the WMAP team. In the COSMOGLOBE processing, this pattern arises from temperature-to-polarization leakage from the coupling between the CMB Solar dipole, transmission imbalance, and sidelobes. No traces of this pattern are found in either the frequency map or TOD residual map, suggesting that the current processing has succeeded in modeling these poorly measured modes within the assumed parametric model by using Planck information to break the sky-synchronous degeneracies inherent in the WMAP scanning strategy.
Global earthquake occurring rate displays an exponential decay down to ~300 km and then peaks around 550 to 600 km before terminating abruptly near 700 km. How fractures initiate, nucleate, and propagate at these depths remains one of the greatest puzzles in earth science, as increasing pressure inhibits fracture propagation. We report nanoseismological analysis on high-resolution acoustic emission (AE) records obtained during ruptures triggered by partial transformation from olivine to spinel in Mg 2 GeO 4 , an analog to the dominant mineral (Mg,Fe) 2 SiO 4 olivine in the upper mantle, using state-of-the-art seismological techniques, in the laboratory. AEs’ focal mechanisms, as well as their distribution in both space and time during deformation, are carefully analyzed. Microstructure analysis shows that AEs are produced by the dynamic propagation of shear bands consisting of nanograined spinel. These nanoshear bands have a near constant thickness (~100 nm) but varying lengths and self-organize during deformation. This precursory seismic process leads to ultimate macroscopic failure of the samples. Several source parameters of AE events were extracted from the recorded waveforms, allowing close tracking of event initiation, clustering, and propagation throughout the deformation/transformation process. AEs follow the Gutenberg-Richter statistics with a well-defined b value of 1.5 over three orders of moment magnitudes, suggesting that laboratory failure processes are self-affine. The seismic relation between magnitude and rupture area correctly predicts AE magnitude at millimeter scales. A rupture propagation model based on strain localization theory is proposed. Future numerical analyses may help resolve scaling issues between laboratory AE events and deep-focus earthquakes.
Sweet sorghum is typically cultivated for the food and fodder market. Recently, sweet sorghum varieties are being metabolically transitioned to enhance energy density by accumulating oil droplets in their vegetative tissues for bioenergy applications. Owing to the high biomass yield of sorghum, the transgenic lines can compete with oil-seed crops for biodiesel yield per unit area. In the initial phase of transgenic development, a high-throughput phenotyping method can bridge the gap between the production pipeline and analysis to improve the efficiency of the process. To meet the requirement, the present study extends the application of time-domain 1H-NMR spectroscopy for rapid quantification and characterization of the total in-situ lipids of sweet sorghum ‘ramada’ to lay the groundwork for analyzing the upcoming large quantity of transgenic samples. NMR technology has been successfully established for analyzing lipid contents of vegetative tissues of non-transgenic variety. The multiexponential analysis of spin-lattice (T1) relaxation spectra obtained from TD-NMR aided the investigation of the dynamics of the free and bound lipid fraction with plant development. The total lipid concentration of bagasse and leaves of non-transgenic sweet sorghum remained unchanged throughout the plant development. Leaves displayed a higher percentage of bound lipids as compared to bagasse. A significant variation in the lipid concentration of juice was observed at the different growth stages with a maximum lipid accumulation of 1.21 ± 0.04% w/w at the boot stage that decreased with further maturity of the plant.
High pressure induces dramatic changes and novel phenomena in condensed volatiles(1,2) that are usually not preserved after recovery from pressure vessels. In this study we report a process that pressurizes volatiles into nanopores of type 1 glassy carbon precursors, converts glassy carbon into nanocrystalline diamond by heating and synthesizes free-standing nanostructured diamond capsules (NDCs) capable of permanently preserving volatiles at high pressures, even after release back to ambient conditions for various vacuum-based diagnostic probes including electron microscopy. As a demonstration, we perform a comprehensive study of a high-pressure argon sample preserved in NDCs. Synchrotron X-ray diffraction and high-resolution transmission electron microscopy show nanometre-sized argon crystals at around 22.0 gigapascals embedded in nanocrystalline diamond, energy-dispersive X-ray spectroscopy provides quantitative compositional analysis and electron energy-loss spectroscopy details the chemical bonding nature of high-pressure argon. The preserved pressure of the argon sample inside NDCs can be tuned by controlling NDC synthesis pressure. To test the general applicability of the NDC process, we show that high-pressure neon can also be trapped in NDCs and that type 2 glassy carbon can be used as the precursor container material. Additional experiments on other volatiles and carbon allotropes open the possibility of bringing high-pressure explorations on a par with mainstream condensed-matter investigations and applications.