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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.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Rapid analysis of 237 Np and Pu isotopes in unseparated sample matrices using ICP-MS/MS

Inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) is an emerging technique for measuring actinide isotopes when assessing pre- and post- detonation nuclear material. In this study, ICP-MS/MS was investigated for direct Np and Pu quantitation in unseparated, dissolved bulk soil matrices. To achieve this, purified nitric oxide (NO) was investigated for the reactivity of Th, Np, U, Pu, Am, and Cm. Purifying NO prior to the collision reaction cell (CRC) results in increased sensitivity and allows for higher gas flows to be utilized for the removal of interferences. Here, the interference from uranium hydrides was mitigated to less than 3.85 x 10 -11 . This method was demonstrated on standard reference materials which were measured for 237 Np and 238,239,240 Pu in dilute sample digestions. The 238 Pu measurement was validated by spiking into a standard reference material and was accurately measured with an excess of 85000 of 238 U.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Evaluation of the Radioactive Material Released in the Harborview Research and Training Building and Some Implications for Emergency Response

On 2 May 2019, during the 137 Cs source recovery operation, a source capsule in a research irradiator containing approximately 77.1 TBq was breached. Based on a geometric reconstruction analysis of the damage to the capsule, approximately 46.3 GBq (0.04%) was impacted by the chop saw (grinder) inside a mobile hot cell on the loading dock at the University of Washington Harborview Research and Training (HRT) Building. A very small fraction of the material impacted, less than 1%, was released from the mobile hot cell and then to the rest of the HRT Building. The objectives of this project were to assess the accidental release of 137 CsCl and its implications related to emergency response methods and the ramifications of 137 CsCl transport. The phenomenology of this event was also compared with past alkali halide dispersal events. The vast number of measurements and samples collected by the remediation contractors, the Department of Energy’s Nuclear Emergency Support Team, and the small number of retrospective samples collected by the authors informed the analysis. The techniques included (1) autoradiography and electron microscopy of samples collected from the HRT Building and the irradiator, (2) 3D visualization of deposition on surfaces and within the ventilation system, and (3) a study of the damage to the source capsule to evaluate the Cs particle size and particle composition due to the grinding accident. Subsequently, the cesium contaminant transport through the numerous pathways in the building was reconstructed to assess the deposition on surfaces as a function of particle size. Furthermore, the implications for emergency response are relevant to data quality and management. A Data Quality Objective guides data collection methods so that they have appropriate accuracy and precision for the intended application. Recommendations were made with respect to the sample collection protocols and archiving of samples.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2024

Spectral Data Fusion From Handheld Laser-Induced Breakdown Spectroscopy (LIBS) and X-ray Fluorescence (XRF) Analyzers for Improved Detection of Cerium in a Simulated Dispersal Accident

Here, this work implements a mid-level data fusion methodology on spectral data from handheld X-ray fluorescence and laser-induced breakdown spectroscopy analyzers to quantify plutonium surrogate (CeO 2 ) contamination in soil samples for the first time. Spectral data from each analyzer were used independently to train supervised machine learning regressions to predict Ce concentration. Fused features from both data sets were then used to train the same models, comparing prediction performance by evaluating model precision and sensitivity. Fusing principal component scores from the two sensors yielded an order of magnitude improvement in precision and sensitivity of predictions made with an artificial neural network, compared to predictions made by models trained on independent sensor data. As a result, a boosted ensemble trained on the fused spectral features yielded an ideal predictor with root-mean-squared error on the order of 10 –6 and calculated limit of detection order 10 –5 wt %.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Evaluation of Properties for Microsample Identification

A study was conducted to determine if individual particle characteristics could be used to identify particles of interest, sub-samples, from bulk post-detonation debris. Three archived post-detonation debris samples were used for this effort. Particles from these samples were identified as active (produced fission tracks), and inactive (did not produce fission tracks), as the first defining characteristic. Morphology was the secondary characteristic to select particles for further study, i.e. spherical/non-spherical. Once particles were identified and isolated, they were characterized by optical microscopy for size in µm, number of fission tracks, morphology, transmitted light color, and reflected light color. Particles were then analyzed by scanning electron microscopy for morphology, elemental content, and compound identification. Raman spectroscopy was attempted on five particles with indeterminate results due to environmental mixing (heterogeneity) during the events of particle formation. Once all non-destructive analyses were completed all particles were analyzed by thermal ionization mass spectrometry to determine isotopic atom percents of plutonium and uranium, and an estimate of atoms of plutonium and uranium in each particle. An estimate of the ratio of uranium to plutonium was also obtained (U/Pu). Data analytics of the data from the particles showed that combining characteristics of the particles have a high probability of identifying particles of interest from bulk post-detonation debris samples. Please note that this version of the report is an abridged version of the full report (Wagnon et al. 2025) that has been edited to be appropriate for public release.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Investigation of the thermal decomposition of Pu(IV) oxalate: a transmission electron microscopy study

The degradation of the internal structure of plutonium (IV) oxalate during calcination was investigated with Transmission Electron Microscopy (TEM), electron diffraction, Electron Energy-Loss Spectroscopy (EELS), and 4D Scanning TEM (STEM). TEM lift-outs were prepared from samples that had been calcined at 300°C, 450°C, 650°C and 950°C. The resulting phase at all calcination temperatures was identified as PuO 2 with electron diffraction. The grain size range was obtained with high-resolution TEM. In addition, 4D STEM images were analyzed to provide grain size distributions. In the 300°C calcined sample, the grains were <10 nm in diameter, at 650°C, the grains ranged from 10 to 20 nm, and by 950°C, the grains were 95–175 nm across. Using the Kolmogorov-Smirnov (K-S) two sample test, it was shown that morphological measurements obtained from 4D-STEM provided statistically significant distributions to distinguish samples at the different calcination conditions. Using STEM-EELS, carbon was shown to be present in the low temperature calcined samples associated with oxalate but had formed carbon (possibly graphite) deposits in the 950°C calcined sample. This work highlights the new methods of STEM-EELS and 4D-STEM for studying the internal structure of special nuclear materials (SNM).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Inverse prediction of PuO2 processing conditions using Bayesian seemingly unrelated regression with functional data

Over the past decade, a variety of innovative methodologies have been developed to better characterize the relationships between processing conditions and the physical, morphological, and chemical features of special nuclear material (SNM). Different processing conditions generate SNM products with different features, which are known as “signatures” because they are indicative of the processing conditions used to produce the material. These signatures can potentially allow a forensic analyst to determine which processes were used to produce the SNM and make inferences about where the material originated. This article investigates a statistical technique for relating processing conditions to the morphological features of PuO 2 particles. We develop a Bayesian implementation of seemingly unrelated regression (SUR) to inverse-predict unknown PuO 2 processing conditions from known PuO 2 features. Model results from simulated data demonstrate the usefulness of the technique. Applied to empirical data from a bench-scale experiment specifically designed with inverse prediction in mind, our model successfully predicts nitric acid concentration, while results for Pu concentration and precipitation temperature were equivalent to a simple mean model. Our technique compliments other recent methodologies developed for forensic analysis of nuclear material and can be generalized across the field of chemometrics for application to other materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Spatially Resolved Raman Spectroscopic Investigation of Uranyl Fluoride: A Case Study in the Importance of Instrument Optimization

Raman spectroscopy is an emerging technique for rapid and nondestructive analysis of nuclear materials for forensic and nonproliferation applications as it is a powerful tool for distinguishing multiple chemical forms of materials with similar stoichiometries. Recent developments in spectroscopic software have enabled rapid data collection with high-speed Raman spectroscopic mapping capabilities. However, some uranium-rich materials are susceptible to degradation in humid air and/or laser-induced phase transformations. To mitigate environmental or measurement-related sample degradation of potential samples of interest, we have taken a systematic approach to define optimized data collection parameters for high-throughput measurements of uranyl fluoride (UO 2 F 2 ), which is an important intermediate material in the nuclear fuel cycle. First, we systematically describe the influence of optical magnification (5× to 100×), laser power, and exposure time on obtained signal for identical particles of UO 2 F 2 and find that at low laser power and exposure times, comparable signal is obtained regardless of optical magnification. Second, we ensure sample integrity during data collection, and third, collect spectroscopic maps that employ optimized parameters to reduce the time required to obtain spatially resolved spectroscopic information. Reductions of 90% and 99% in measurement times are discussed as they relate to differences in resolving spectroscopic features of particles in identical mapping areas. Finally, during this work, we found that additional data processing options were needed and thus developed a customized Python script for importing, processing, analyzing, and visualizing Raman spectroscopic map data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Development of a Flow-through Cell for Ultrasonic Extraction (UE)─Single Particle (SP)─ICP-MS─an Approach for Nano/Microparticle Elemental and Isotopic Analysis

Nanotechnology is a salient part of the scientific landscape, and analytical approaches are rapidly evolving to enable small-scale characterization of nano- and microparticle compositions and impurities. Here, a flow-through sonicating cell was developed for direct particle extraction from a silicon wafer and integrated with an inductively coupled plasma–mass spectrometer (ICP-MS) for subsequent elemental and isotopic characterization of the released particles. Ultrasonic extraction (UE)─single particle (SP)─ICP-MS offers controlled particle mobilization from solid substrates and allows for increased sample throughput by eliminating the need for pre-extraction of particles and decreasing sample preparation steps. Coupling this device to an ICP-MS with a time-of-flight (TOF) mass analyzer, it is possible to distinguish unique isotopic compositions of the particles. Both tungsten and nickel isotopically tagged particles, which were deposited on Si wafers, are presented here with analysis via UE─SP─ICP-MS. This approach could support efforts in the fields of particle synthesis, nuclear safeguards and forensics, environmental monitoring, and semiconductor industries in which the detection of particles from substrates and wafers is critical.

Paul, Molly [ORNL] (ORCID:0009000009672055)↗
DOE OSTI2024

Fuel Performance Calculations of Tagged UO 2 MiniFuel Disks

Isotopic taggants are being considered as a novel form of forensic identifiers for nuclear fuels. As part of this effort, eighteen tagged MiniFuel disks were irradiated in the High Flux Isotope Reactor at Oak Ridge National Laboratory. In this work, the BISON fuel performance code was used to recreate the pellets and predict their behavior and their post-irradiation material properties. These predictions are to serve as a baseline to help investigators identify results of interest during post-irradiation examination of actual MiniFuel disks. The simulation methodology and models are described herein, along with the individual disk predictions. Several general trends were identified in this analysis. Based on the models, it is predicted that the pellets’ internal temperatures will rise over time, fission gas release will remain constant at around 1%, regardless of the burnup, and no grain growth will occur in any of the disks. The reasons for these predictions are discussed below. Probable shortcomings in the BISON predictions are addressed, and future work is proposed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Advances in geophysical forensic event monitoring

Forensic analysis of man-made, non-nuclear events (such as industrial accidents, explosion experiments and mine collapses) has become more frequent and detailed owing to advancements in geophysical monitoring. Here, in this Technical Review, we demonstrate how geophysical forensic monitoring using seismic, infrasound and hydroacoustic recordings provides insights on events in the solid earth, atmosphere and underwater. Advanced techniques, including machine-learning-based models, have been developed to detect, identify and investigate these events, providing information on location, subevents, sources and explosive yield. The increase in data availability, application of advanced methods and computation and the growth of multitechnology approaches have increased the accuracy of forensic event analysis and enabled more realistic characterization of uncertainties. For example, the 2020 Beirut explosion in Lebanon demonstrated that various seismic, acoustic and other methods could be used to estimate explosive yield (and yield uncertainties) of about 1 ktonne, providing confidence in the application of these methods to smaller events where data are available. However, forensic investigations remain largely limited to known events with identified sources. Increased access to data, sophisticated analysis methods and high-resolution earth models will improve forensic event analysis further, enabling civil and scientific applications, such as localization in the search for the lost ARA San Juan submarine.

geophysics↗
DOE OSTI2026

U.S. Efforts in Support of Examinations at Fukushima Daiichi - November 2025 Meeting Notes

Fifteen years have passed since the March 11, 2011, the Great East Japan Earthquake (GEJE) triggered a tsunami that inundated the Fukushima Daiichi Nuclear Power Station (Daiichi or 1F) and led to severe accidents in multiple units at the plant. During these fifteen years since these events, Daiichi forensics examinations and evaluations have revealed many insights for enhancing the safety of nuclear power plants worldwide. However, uncertainties remain regarding the events after the GEJE. Additional Daiichi forensics information is required to inform future Decontamination and Decommissioning (D&D) activi- ties conducted by the plant owner, Tokyo Electric Power Company Holdings, Incorporated (TEPCO Hold- ings). This forensics information also has important implications for the safety and operation of U.S. commercial nuclear power plants. A collaborative U.S. and Japanese effort, which includes approximately 50 experts in reactor safety and plant operations, was initiated in 2014 by the Department of Energy Office of Nuclear Energy (U.S. DOE-NE) to identify Daiichi examination needs and evaluate recent Daiichi examination data to address these needs. This collaborative effort, which is beneficial to the U.S. and Japan, continues as Japan moves forward with D&D activities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Automated nuclear cloud feature extraction from film

Chemical, biological, radiological, nuclear, and explosives incidents require rapid detection and characterization for appropriate response. For a nuclear detonation, visible-light cameras may be used to locate the cloud and characterize fallout deposition when coupled with numerical models. Films from the United States’ nuclear testing era compose the only sizeable collection of imagery depicting high-yield detonations. These films offer unique insights into characteristics of flows involving scales that are difficult to replicate experimentally, and they are a valuable source of data for the validation of models for nuclear fallout transport, either as part of emergency response or forensic activities. In this work, we implement modern computer vision and machine learning techniques to identify and track the cloud automatically and subsequently determine the time dependence of some of its features. We trained a ResNet-18 image classifier on hundreds of images to categorize nuclear cloud morphology. Each category or cloud regime is determined by early cloud evolution and is associated to constitutive properties of the flow, such as distribution of vorticity. Next, we identified keypoint features using the KAZE algorithm and tracked these keypoints in the images, allowing us to determine the dimensions and velocities of the cloud across film frames. These measurements converted to real-world units provide valuable experimental data that can be used in the development and validation of nuclear cloud models. We compared the results of this method against manual cloud rise measurements from two different films. In one, our automated method accelerated the feature extraction process without sacrificing measurement accuracy.

Khristy, Joel [ORNL] (ORCID:0000000209963060)↗
DOE OSTI2024

SEDONA and ERDE: Portable Detection of Chemical Agents by Low Magnetic Field Nuclear Magnetic Resonance [Slides]

Two spectrometer systems have been developed at LANL for hazardous and/or toxic chemical agent detection and forensic analysis: SpEctroscopic Detection Of Nerve Agents (SEDONA) is a portable bottle scanner; and Earth’s field Resonance Detection and Evaluation (ERDE) Devices are fieldable J-coupled Earth’s Field - NMR (EF-NMR) spectrometers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗