Search NASA⌕ Search

SEARCH · Search NASA

Results for “Visual Analytics Environments”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

An investigation of airflow over the aft portions of a variable sweep fighter configuration

An investigation of air flow over the aft portions of a variable sweep fighter aircraft configuration was made. Tests conducted in the unitary plan wind tunnel at Mach number 2.16 included measurements of forces, moments, and local static pressures as well as visual recordings of the air flow. An aerodynamic analytical prediction method was evaluated when used in data comparison at angles of attack of 0, 5, and 15 degrees. The results indicate that in supersonic flow the typical outboard located twin vertical tail arrangement tends to provide a more positive increment in normal-force on the afterbody fuselage and the horizontal tail than a single center-mounted vertical tail of similar planform shape. In addition, the results indicate that a method for aerodynamic analysis of wing-body-tail configurations currently available can provide reasonable estimates of pressure coefficient distributions on configurations in regions of complex supersonic flow. At this time, however, the available analytical method cannot adequately replace experimental wind tunnel tests for determining the supersonic flow environment of a given configuration.

Graves, E. B.↗
DOE OSTI2018

Hybrid Polymer/Metal–Organic Framework Films for Colorimetric Water Sensing over a Wide Concentration Range [Hybrid Polymer/MOF Films for Colorimetric Water Sensing over a Wide Concentration Range]

Because of their extraordinary surface areas and tailorable porosity, metal–organic frameworks (MOFs) have the potential to be excellent sensors of gas-phase analytes. MOFs with open metal sites are particularly attractive for detecting Lewis basic atmospheric analytes, such as water. Here, we demonstrate that thin films of the MOF HKUST-1 can be used to quantitatively determine the relative humidity (RH) of air using a colorimetric approach. HKUST-1 thin films are spin-coated onto rigid or flexible substrates and are shown to quantitatively determine the RH within the range of 0.1–5% RH by either visual observation or a straightforward optical reflectivity measurement. At high humidity (>10% RH), a polymer/MOF bilayer is used to slow the transport of H 2 O to the MOF film, enabling quantitative determination of RH using time as the distinguishing metric. Lastly, the sensor is combined with an inexpensive light-emitting diode light source and Si photodiode detector to demonstrate a quantitative humidity detector for low humidity environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

NanoSIP: NanoSIMS Applications for Microbial Biology

High-resolution imaging with secondary ion mass spectrometry (nanoSIMS) has become a standard method in systems biology and environmental biogeochemistry and is broadly used to decipher ecophysiological traits of environmental microorganisms, metabolic processes in plant and animal tissues, and cross-kingdom symbioses. When combined with stable isotope-labeling—an approach we refer to as nanoSIP—nanoSIMS imaging offers a distinctive means to quantify net assimilation rates and stoichiometry of individual cell-sized particles in both low- and high-complexity environments. While the majority of nanoSIP studies in environmental and microbial biology have focused on nitrogen and carbon metabolism (using 15 N and 13 C tracers), multiple advances have pushed the capabilities of this approach in the past decade. The development of a high-brightness oxygen ion source has enabled high-resolution metal analyses that are easier to perform, allowing quantification of metal distribution in cells and environmental particles. New preparation methods, tools for automated data extraction from large data sets, and analytical approaches that push the limits of sensitivity and spatial resolution have allowed for more robust characterization of populations ranging from marine archaea to fungi and viruses. Further, NanoSIMS studies continue to be enhanced by correlation with orthogonal imaging and ‘omics approaches; when linked to molecular visualization methods, such as in situ hybridization and antibody labeling, these techniques enable in situ function to be linked to microbial identity and gene expression. Here we present an updated description of the primary materials, methods, and calculations used for nanoSIP, with an emphasis on recent advances in nanoSIMS applications, key methodological steps, and potential pitfalls.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2018

Hierarchical visualization of materials space with graph convolutional neural networks

The combination of high throughput computation and machine learning has led to a new paradigm in materials design by allowing for the direct screening of vast portions of structural, chemical, and property spaces. The use of these powerful techniques leads to the generation of enormous amounts of data, which in turn calls for new techniques to efficiently explore and visualize the materials space to help identify underlying patterns. In this work, we develop a unified framework to hierarchically visualize the compositional and structural similarities between materials in an arbitrary material space with representations learned from different layers of graph convolutional neural networks. We demonstrate the potential for such a visualization approach by showing that patterns emerge automatically that reflect similarities at different scales in three representative classes of materials: perovskites, elemental boron, and general inorganic crystals, covering material spaces of different compositions, structures, and both. For perovskites, elemental similarities are learned that reflects multiple aspects of atom properties. For elemental boron, structural motifs emerge automatically showing characteristic boron local environments. For inorganic crystals, the similarity and stability of local coordination environments are shown combining different center and neighbor atoms. The method could help transition to a data-centered exploration of materials space in automated materials design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

SAFE-OCC: A novelty detection framework for Convolutional Neural Network sensors and its application in process control

Herein we present a novelty detection framework for Convolutional Neural Network (CNN) sensors that we call Sensor-Activated Feature Extraction One-Class Classification (SAFE-OCC). We show that this framework enables the safe use of computer vision sensors in process control architectures. Emergent control applications use CNN models to map visual data to a state signal that can be interpreted by the controller. Incorporating such sensors introduces a significant system operation vulnerability because CNN sensors can exhibit high prediction errors when exposed to novel (abnormal) visual data. Unfortunately, identifying such novelties in real-time is nontrivial. To address this issue, the SAFE-OCC framework leverages the convolutional blocks of the CNN to create an effective feature space to conduct novelty detection using a desired one-class classification technique. This approach engenders a feature space that directly corresponds to that used by the CNN sensor and avoids the need to derive an independent latent space. We demonstrate the effectiveness of SAFE-OCC via simulated control environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Frequent Fulcrum Functions: The Basics of SCALE’s Graphical User Interface [Slides]

This tutorial introduces the Fulcrum graphical user interface and the basic functions that enhance the common activities of creating, editing, navigating, executing, and visualizing SCALE input files. This tutorial will help you become familiar with the Fulcrum input file text editor and the integrated input development environment features of autocompletion, automatic checking, cursor context, and input navigation. In addition, the Fulcrum and SCALE runtime environment will be reviewed to improve the understanding of job execution workflow. This tutorial does not cover data and geometry plotting. Please see the Advanced User Interface Capabilities tutorial for details regarding plotting data and geometry. No prior experience with SCALE is required. You can follow along using SCALE 6.2 or 6.3-beta.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Competing Pathways for Nucleation of the Double Perovskite Structure in the Epitaxial Synthesis of La 2 MnNiO 6

Over the past decades a confluence of advanced synthesis techniques, data-driven characterization, and rapid increases in computing power has sparked a renaissance in materials engineering. The emerging “materials-by-design” approach, while radically transforming the development of multicomponent systems, has tended to overlook the complex kinetic pathways that define materials synthesis. Although we are able to envision almost limitless materials combinations, we are unable to synthesize all of them in practice, since existing characterization and modeling approaches often fail to capture the inherent complexity of such systems. There is currently a disconnect between highly local structural characterization and macroscale properties measurements, resulting in oversimplified or incomplete structure-property models. Here we describe a multi-technique approach that combines aberration-corrected transmission electron microscopy with emerging oxide atom probe tomography to measure chemical ordering and extended defects in the model complex oxide, La2MnNiO6. We visualize cation ordering, as well as a three-dimensional network of secondary phases, which we describe in terms of ab initio structure calculations. We propose a defect model in which these phases alter their surrounding octahedral environment, severely disrupting cation superexchange. Through this array of experimental and theoretical techniques, we uncover fundamental structure-property relationships and illustrate a new approach to engineer complex, multicomponent systems.

atom probe tomography↗
DOE OSTI2024

Focused Ion Beam Tomography of Alloy 617 Corroded in Molten Chloride Salt

Materials qualification of reactor structural materials is a critical step in rapid implementation of advanced nuclear reactor technologies, particularly to assess the corrosion performance in these designs. Accelerated qualification of reactor structural materials requires incorporating powerful computational toolsets, such as phase field modelling in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, to predict the evolution of structural materials due to corrosion. Accordingly, computational toolsets will require experimental data generated at appropriate length scales to validate accuracy. Focused ion beam (FIB) provides a high degree of control over manipulation of materials for analytical purposes, including capturing data on the evolution in the microstructure and elemental composition of materials at the mesoscale, an appropriate length scale for phase field modelling of intergranular diffusion phenomena using the MOOSE framework. For instance, the FEI Helios G4 UX dual beam plasma FIB microscope at the Irradiated Materials Characterization Laboratory (IMCL) is capable of backscatter diffraction (EBSD) and energy-dispersive x-ray spectroscopy (EDS) documenting the evolution in the microstructure and elemental composition, respectively. The Helios can perform EDS and EBSD three-dimensionally (3D) using tomography, which is then combined using different software packages to visualize 3D volumes correlating elemental composition to microstructural data. The purpose of this investigation was to develop a streamlined characterization and data processing workflow for 3D tomography studies on the FEI Helios G4 plasma FIB. The investigation is segmented into three parts: 1) Optimizing the data collection workflow, 2) identifying appropriate data processing and visualization software (i.e. DREAM.3D, MIPAR, and VGStudioMax), and 3) establishing an infrastructure for public release. The optimization of the data collection workflow is in collaboration with members of the U220 department to setup formal training on the tomography operation of the G4, through ThermoFisher Scientific, and exploring DREAM.3D, MIPAR, and VGStudioMax data processing/visualization software packages. VGStudioMax currently demonstrates the most promise for future use. Optimization of the data collection and processing workflow is still ongoing. A collaboration with INL High Performance Computing (HPC) established an open-source license for expediting the public release of FIB tomography datasets through HPC. FIB tomography data generated by the G4 will provide comprehensive data for validating 3D phase field mesoscale modelling tools within the MOOSE framework for accelerated qualification of reactor structural materials.

Copeland-Johnson, Trishelle↗
NASA NTRS1996

Tilt Rotor Aircraft Aeroacoustics

A fleet of civil tilt rotor transports offers a means of reducing airport congestion and point-to-point travel time. The speed, range, and fuel economy of these aircraft, along with their efficient use of vertiport area, make them good candidates for short-to-medium range civil transport. However, to be successfully integrated into the civilian community, the tilt rotor must be perceived as a quiet, safe, and economical mode of transportation that does not harm the environment. In particular, noise impact has been identified as a possible barrier to the civil tilt rotor. Along with rotor conversion-mode flight, and blade-vortex interaction noise during descent, hover mode is a noise problem for tilt rotor operations. In the present research, tilt rotor hover aeroacoustics have been studied analytically, experimentally, and computationally. Various papers on the subject were published as noted in the list of publications. More recently, experimental measurements were made on a 1/12.5 scale model of the XV-15 in hover and analyses of this data and extrapolations to full scale were also carried out. A dimensional analysis showed that the model was a good aeroacoustic approximation to the full-scale aircraft, and scale factors were derived to extrapolate the model measurements to the full-scale XV-15. The experimental measurements included helium bubble flow visualization, silk tuft flow visualization, 2-component hot wire anemometry, 7-hole pressure probe measurements, vorticity measurements, and outdoor far field acoustic measurements. The hot wire measurements were used to estimate the turbulence statistics of the flow field into the rotors, such as length scales, velocity scales, dissipation, and turbulence intermittency. Several different configurations of the model were tested: (1) standard configurations (single isolated rotor, two rotors without the aircraft, standard tilt rotor configuration); (2) flow control devices (the 'plate', the 'diagonal fences'); (3) basic configuration changes (increasing the rotor/rotor spacing, reducing the rotor plane/wing clearance. operating the rotors out of phase). Also, an approximation to Sikorsky's Variable Diameter Tilt Rotor (VDTR) configuration was tested, and some flow measurements were made on a semi-span configuration of the model. Acoustic predictions were made using LOWSON.M, a Mathematica code Mean aerodynamic models were developed based on hover performance predictions from HOVER.FOR. This hover prediction code used blade element theory for the aerodynamics, and Prandtl's Vortex theory to model the wake, along with empirical formulas for the effects of Reynolds number, Mach number, and stall. Aerodynamic models were developed from 7-hole pressure probe measurements of the mean velocity into the model rotors.

George, Albert R.↗
NASA NTRS2015

TankSIM: A Cryogenic Tank Performance Prediction Program

Accurate prediction of the thermodynamic state of the cryogenic propellants in launch vehicle tanks is necessary for mission planning and successful execution. Cryogenic propellant storage and transfer in space environments requires that tank pressure be controlled. The pressure rise rate is determined by the complex interaction of external heat leak, fluid temperature stratification, and interfacial heat and mass transfer. If the required storage duration of a space mission is longer than the period in which the tank pressure reaches its allowable maximum, an appropriate pressure control method must be applied. Therefore, predictions of the pressurization rate and performance of pressure control techniques in cryogenic tanks are required for development of cryogenic fluid long-duration storage technology and planning of future space exploration missions. This paper describes an analytical tool, Tank System Integrated Model (TankSIM), which can be used for modeling pressure control and predicting the behavior of cryogenic propellant for long-term storage for future space missions. It is written in the FORTRAN 90 language and can be compiled with any Visual FORTRAN compiler. A thermodynamic vent system (TVS) is used to achieve tank pressure control. Utilizing TankSIM, the following processes can be modeled: tank self-pressurization, boiloff, ullage venting, and mixing. Details of the TankSIM program and comparisons of its predictions with test data for liquid hydrogen and liquid methane will be presented in the final paper.

Bolshinskiy, L. G.↗
DOE OSTI2016

High-performance oxygen reduction and evolution carbon catalysis: From mechanistic studies to device integration

The development of high-performance and low-cost oxygen reduction and evolution catalysts that can be easily integrated into existing devices is crucial for the wide deployment of energy storage systems that utilize O 2 -H 2 O chemistries, such as regenerative fuel cells and metal-air batteries. Herein, we report an NH 3 -activated N-doped hierarchical carbon (NHC) catalyst synthesized via a scalable route, and demonstrate its device integration. The NHC catalyst exhibited good performance for both the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER), as demonstrated by means of electrochemical studies and evaluation when integrated into the oxygen electrode of a regenerative fuel cell. The activities observed for both the ORR and the OER were comparable to those achieved by state-of-the-art Pt and Ir catalysts in alkaline environments. We have further identified the critical role of carbon defects as active sites for electrochemical activity through density functional theory calculations and high-resolution TEM visualization. As a result, this work highlights the potential of NHC to replace commercial precious metals in regenerative fuel cells and possibly metal-air batteries for cost-effective storage of intermittent renewable energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Determine the coordination of Al and Si of Fe-rich fly ash: The challenge in NMR and how we probe its heterogeneity using X-ray spectromicroscopy

Scanning transmission X-ray microscopy (STXM) coupled with ptychographic imaging at Al and Si K-edge is a new probe to the microscale chemistry of heterogenous materials. Here, the combined techniques are applied to study local coordination environment of Fe-rich fly ash (FA). Ptychographic imaging at Al K- and Si K-edge highlights the fine Al- and Si-rich morphological features, respectively, at 6 nm pixel resolution. STXM visualizes the inter- and intra-particle variations in the silicate polymerization degree and two types of Al coordination environment in FA. The Si K-edge of SiO4 connected with four-fold coordinated Al is higher than SiO4 sharing oxygen with six-fold coordinated Al. The result is consistent with bulk nuclear magnetic resonance spectroscopy measurement of the Fe-rich sample which, however, is sensitive to paramagnetic Fe and time-consuming. Here, we demonstrate that the combined method has great potential in the studies of chemically heterogenous aluminosilicates.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2018

Development of a Technology Roadmap for Online Monitoring of Nuclear Power Plants

The nuclear power industry has recently recognized the potential cost saving that can be achieved from migrating the current manual and labor dependent surveillance and preventive maintenance activities to data-driven online monitoring methods. Since then, several efforts have been launched with various degrees of momentum to tackle specific surveillance or preventive maintenance activities. The light water reactor sustainability program (LWRS) program has anticipated this need and launched an effort that aimed to develop a technology roadmap for the nuclear power industry. Because the roadmap has to be focused towards the user or application’s value, and because nuclear power plants have different process efficiencies and deficiencies, the technology roadmap has to be plant independent. Achieving this objective required optimizing the extent of details described by a technology roadmap. The approach followed is for the roadmap to describe the sequence of activities needed to automate a process or equipment activity, but not describe the sequence of processes or equipment to target. For example, the steps required to migrate the inspection of a pump are plant independent. However, defining that the migration of feed water pumps inspections to online monitoring should be performed before inspections of feed water valves is dependent on multiple plant factors such as the plant requirements, labor work capacity, and process or equipment conditions. The technology roadmap was broken down into six elements, four of which have a sequential path of advancement, while the other two are supporting elements to the sequential elements. The sequential part of the roadmap analyzes data collection, analytics, visualization, and management. For these elements of the technology roadmap, the migration of an activity is defined in three states. The base state is defined as the most primitive, manual, and labor dependent process used by some nuclear power plants. The modern state is defined as the state that can be achieved if the activities are augmented or replaced by current technologies that are commercially available or are soon to be available. The state of the art is defined as using technologies of the future, i.e. concept and technologies that are being researched. The data collection part of the technology roadmap defines three states of every process performed in a nuclear power plant. However, the data analytics part is described based on equipment, because automating an activity performed on one equipment required considering multiple data sources. The visualization and data management elements are process or equipment independent. Visualization describes the means to use human factor science and technologies advancement in presenting the data collected and the data analytics results. The data management targets storage, communication, and computational power need, in addition to data integration and sharing. Since storage, communication, and computational power technologies and path for deployment are known to any information technology organization, this effort targeted the cost of data management. This has a direct impact on the feasibility of the automation effort. The supporting elements analyzes the value of automating the activity and the change challenges to tackle. For the support elements, the roadmap targeted describing activities that need to be performed as part of the roadmap development. The value element of the roadmap describes how to analyze the cost saving and the associated risk. The change management identifies multiple factors to consider such as regulation, cybersecurity, resource availability, supporting infrastructure availability, feasibility (power, fitness, environment tolerance, facilities), and cultural change.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1994

In-flight imaging of transverse gas jets injected into transonic and supersonic crossflows: Design and development

The design and development of an airborne flight-test experiment to study nonreacting gas jets injected transversely into transonic and supersonic crossflows is presented. Free-stream/crossflow Mach numbers range from 0.8 to 2.0. Planar laser-induced fluorescence (PLIF) of an iodine-seeded nitrogen jet is used to visualize the jet flow. Time-dependent images are obtained with a high-speed intensified video camera synchronized to the laser pulse rate. The entire experimental assembly is configured compactly inside a unique flight-test-fixture (FTF) mounted under the fuselage of the F-104G research aircraft, which serves as a 'flying wind tunnel' at NASA Dryden Flight Research Center. The aircraft is flown at predetermined speeds and altitudes to permit a perfectly expanded (or slightly underexpanded) gas jet to form just outside the FTF at each free-stream Mach number. Recorded gas jet images are then digitized to allow analysis of jet trajectory, spreading, and mixing characteristics. Comparisons will be made with analytical and numerical predictions. This study shows the viability of applying highly sophisticated groundbased flow diagnostic techniques to flight-test vehicle platforms that can achieve a wide range of thermo/fluid dynamic conditions. Realistic flow environments, high enthalpies, unconstrained flowfields, and moderate operating costs are also realized, in contrast to traditional wind-tunnel testing.

Wang, Kon-Sheng Charles↗
DOE OSTI2024

Architecture for Web-Based Visualization of Large-Scale Energy Domains: Preprint

With the growing penetration of inverter-based distributed energy resources and increased loads through electrification, power systems analyses are becoming more important and more complex. Moreover, these analyses increasingly involve the combination of interconnected energy domains with data that are spatially and temporally increasing in scale by orders of magnitude, surpassing the capabilities of many existing analysis and decision-support systems. We present the architectural design, development, and application of a high-resolution web-based visualization environment capable of cross-domain analysis of tens of millions of energy assets, focusing on scalability and performance. Our system supports the exploration, navigation, and analysis of large data from diverse domains such as electrical transmission and distribution systems, mobility and electric vehicle charging networks, communications networks, cyber assets, and other supporting infrastructure. We evaluate this system across multiple use cases, describing the capabilities and limitations of a web-based approach for high-resolution energy system visualizations.

grid modernization↗
DOE OSTI2020

Nanoscale Mass Spectrometry Multimodal Imaging via Tip-Enhanced Photothermal Desorption

Materials ranging from adhesives, pharmaceuticals, lubricants, and personal care products are traditionally studied using macroscopic characterization techniques. However, their functionality is in reality defined by details of chemical organization on often noncrystalline matter with characteristic length scales on the order of microns to nanometers. Additionally, these materials are traditionally difficult to analyze using standard vacuum-based approaches that provide nanoscale chemical characterization due to their volatile and beam-sensitive nature. Therefore, approaches that operate under ambient conditions need to be developed that allow probing of nanoscale chemical phenomena and correlated functionality. Here, we demonstrate a tool for probing and visualizing local chemical environments and correlating them to material structure and functionality using advanced multimodal chemical imaging on a combined atomic force microscopy (AFM) and mass spectrometry (MS) system using tip-enhanced photothermal desorption with atmospheric pressure chemical ionization (APCI). We demonstrate enhanced performance metrics of the technique for correlated imaging and point sampling and illustrate the applicability for the analysis of trace chemicals on a human hair, additives in adhesives on paper, and pharmaceuticals samples notoriously difficult to analyze in a vacuum environment. Overall, this approach of correlating local chemical environments to structure and functionality is key to advancing research in many fields ranging from biology, to medicine, to material science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Machine Learning-Guided Approach for Studying Solvation Environments

Molecular-level understanding and characterization of solvation environments are often needed across chemistry, biology, and engineering. Toward practical modeling of local solvation effects of any solute in any solvent, in this work, we report a static and all-quantum mechanics-based cluster-continuum approach for calculating single-ion solvation free energies. This approach uses a global optimization procedure to identify low-energy molecular clusters with different numbers of explicit solvent molecules and then employs the smooth overlap for atomic positions learning kernel to quantify the similarity between different low-energy solute environments. From these data, we use sketch maps, a nonlinear dimensionality reduction algorithm, to obtain a two-dimensional visual representation of the similarity between solute environments in differently sized microsolvated clusters. After testing this approach on different ions having charges 2+, 1+, 1–, and 2–, we find that the solvation environment around each ion can be seen to usually become more similar in hand with its calculated single-ion solvation free energy. Without needing either dynamics simulations or an a priori knowledge of local solvation structure of the ions, this approach can be used to calculate solvation free energies within 5% of experimental measurements for most cases, and it should be transferable for the study of other systems where dynamics simulations are not easily carried out.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Probing the hydrolytic degradation of UF 4 in humid air

This manuscript describes the chemical transformations that occur during hydrolysis of uranium tetrafluoride (UF 4 ) due to its storage in humid air (85% and 50% relative humidity) at ambient temperatures. This hydrolysis was previously reported to proceed slowly or not at all (depending on the percent relative humidity); however, previous reports relied primarily on X-ray diffraction methods to probe uranium speciation. Here, we employ a battery of physiochemical probing techniques to explore potential hydrolysis, including Raman spectroscopy, powder X-ray diffraction, 19 F nuclear magnetic resonance spectroscopy, scanning electron microscopy, and focused ion beam microscopy with energy-dispersive X-ray spectroscopy. Of these, only Raman spectroscopy proved to be particularly useful at observing chemical changes to UF 4 . It was found that anhydrous UF 4 slightly oxidizes over the course of thirteen days to Schoepite-like uranium complexes and possibly UO 3 . In contrast, UF 4 exposed to 50% relative humidity slightly decomposes into UO 2 F 2 , Schoepite-like uranium complexes, and possibly a high order uranium oxide that eluded chemical assignment (U x O y ). Despite the rich chemical speciation observed in our Raman spectroscopy measurements, X-ray diffraction and 19 F NMR measurements on the same material showed no changes. Microscopy measurements suggest that the observed reactions between UF 4 and water occur primarily on the surface of UF 4 particulates via a method that is visually similar to surface corrosion of metals. Therefore, we postulate that NMR spectroscopy and X-ray diffraction, which are well-suited for bulk analysis, are less suited than Raman spectroscopy to observe the surface-based reactions that occur to UF 4 when exposed to humid air. Considering the importance of UF 4 in the production of nuclear fuel and weapons, the results presented herein are widely applicable to numerous nuclear science fields where uranium detection and speciation in humid environments is of value, including nuclear nonproliferation and nuclear forensics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗